U.S. patent application number 15/812951 was filed with the patent office on 2018-03-08 for modeling network signaling in a mobile network.
The applicant listed for this patent is Seven Networks, LLC. Invention is credited to Ari Backholm, Andrey Shvayka.
Application Number | 20180069764 15/812951 |
Document ID | / |
Family ID | 52133391 |
Filed Date | 2018-03-08 |
United States Patent
Application |
20180069764 |
Kind Code |
A1 |
Backholm; Ari ; et
al. |
March 8, 2018 |
MODELING NETWORK SIGNALING IN A MOBILE NETWORK
Abstract
The disclosed technology includes systems and methods for
modeling signaling and/or connections in a mobile network, and
specifically, the benefits of any optimization technique on the
traffic including signals and/or connections in the mobile network.
Embodiments can allocate signaling to specific applications (e.g.,
to determine which applications are chatty and which can cause
problematic signaling), and/or to further model the optimizations
or savings utilizing the disclosed traffic optimization technology.
In some embodiments, to enable or enhance the performance of the
data traffic and signal optimization for the network, the disclosed
technology includes one or more fields (e.g., an expanded fields)
that are calculated by, for example, a analysis core module, to
define and identify at least: (1) whether a transaction causes a
connection (and thus signaling); and (2) the number of connections
that are reduced or saved by the disclosed embodiments of
distributed caching and proxy system.
Inventors: |
Backholm; Ari; (Los Altos,
CA) ; Shvayka; Andrey; (Kiev, UA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Seven Networks, LLC |
Marshall |
TX |
US |
|
|
Family ID: |
52133391 |
Appl. No.: |
15/812951 |
Filed: |
November 14, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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14295289 |
Jun 3, 2014 |
9819552 |
|
|
15812951 |
|
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|
|
61842279 |
Jul 2, 2013 |
|
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04L 41/0893 20130101;
H04L 43/10 20130101; H04L 41/145 20130101 |
International
Class: |
H04L 12/24 20060101
H04L012/24 |
Claims
1. A method of modeling signaling in a mobile network, the method
comprising: determining if transactions initiated by mobile
applications executing on a mobile device in the mobile network
cause network signaling requiring a corresponding radio connection,
wherein at least a portion of the network signaling caused by the
transactions is filtered by a traffic optimization engine; and
modeling the network signaling for the mobile device based, at
least in part, on the filtered network signaling.
2. The method of claim 1, wherein the filtered network signaling
does not cause a corresponding radio connection.
3. The method of claim 1, wherein modeling the network signaling
for the mobile device further comprises calculating signaling
efficiency indicating a total number of the radio connections that
are saved as a result of the filtering.
4. The method of claim 3, wherein calculating the signaling
efficiency further comprises: accessing a radio log and a traffic
activity log associated with the mobile device; modeling a quantity
of virtual radio connections based on the radio log and the traffic
activity log, wherein the virtual radio connections indicate radio
connections that would occur but for said filtering; determining a
quantity of actual radio connections based on the radio log,
wherein the total number of the radio connections that are saved
comprises the difference between the quantity of virtual radio
connections and the quantity of actual radio connections.
5. The method of claim 1, wherein modeling the network signaling
for the mobile device further comprises calculating a time
connected efficiency indicating a total radio connection time saved
as a result of the filtering.
6. The method of claim 5, wherein calculating the time connected
efficiency further comprises: accessing a radio log and a traffic
activity log associated with the mobile device; modeling a virtual
radio time connected based on the radio log and the traffic
activity log, wherein the virtual radio time connected indicates an
amount of time that the mobile device radio would be active but for
said filtering; determining an actual radio time connected based on
the radio log, wherein the actual radio time connected indicates an
amount of time that the mobile device radio is active; wherein the
total radio connection time saved comprises the difference between
the virtual radio time connected and the actual radio time
connected.
7. The method of claim 1, further comprising: tracking the
transactions initiated by the mobile applications executing on the
mobile device in the mobile network.
8. The method of claim 1, further comprising: applying, by the
traffic optimization engine, a traffic optimization technique to
filter the network signaling such that at least the portion of the
network signaling is filtered.
9. The method of claim 1, further comprising: accessing traffic
activity logs indicating traffic metrics measured at multiple
traffic measurement points in the mobile device, wherein modeling
the network signaling further comprises calculating a connection
status and a time connected interval based on the traffic
metrics.
10. The method of claim 1, wherein modeling the network signaling
for the mobile device further comprises attributing the network
signaling to individual applications of the mobile applications
executing on the mobile device.
Description
CROSS REFERENCE TO RELATED APPLICATION
[0001] This application is a continuation of U.S. patent
application Ser. No. 14/295,289 entitled "MODELING NETWORK
SIGNALING IN A MOBILE NETWORK" filed on Jun. 3, 2014, being issued
as U.S. Pat. No. 9,819,552 on Nov. 14, 2017, which claims benefit
of and priority to U.S. Provisional Patent Application No.
61/842,279 entitled "Signaling or Connection Modeling In A Mobile
Network" which was filed on Jul. 2, 2013, the entire contents of
all of which are incorporated by reference herein.
BACKGROUND
Field of Invention
[0002] The present invention relates to modeling network signaling
in a mobile network, and more specifically, to applying a traffic
optimization technique to filter the network signaling and modeling
the signaling and/or connections in the mobile network to determine
the benefits of the optimization technique on the traffic including
signals and/or connections in the mobile network.
Description of Related Art
[0003] In order to address mobile network congestion, it is ideal
to be able to enforce network management policies or corrective
actions on the devices which are in specific congested areas.
Unfortunately, the corrective actions are currently
indiscriminately applied to the devices. This presents a challenge
as indiscriminate application of corrective actions can negatively
impact end-user experience.
BRIEF DESCRIPTION OF THE DRAWINGS
[0004] FIG. 1A illustrates an example diagram of a system where a
host server facilitates management of traffic, content caching,
and/or resource conservation between mobile devices (e.g., wireless
devices), an application server or content provider, or other
servers such as an ad server, promotional content server, or an
e-coupon server in a wireless network (or broadband network) for
resource conservation.
[0005] FIG. 1A-1 illustrates an example diagram illustrating a
general architectural overview of a distributed Open Channel
system.
[0006] FIG. 1B illustrates an example diagram of a proxy and cache
system distributed between the host server and device which
facilitates network traffic management between a device, an
application server or content provider, or other servers such as an
ad server, promotional content server, or an e-coupon server for
resource conservation and content caching.
[0007] FIG. 1C illustrates an example diagram of the logical
architecture of a distributed proxy and cache system.
[0008] FIG. 1D illustrates an example diagram showing the
architecture of client side components in a distributed proxy and
cache system.
[0009] FIG. 1E illustrates a diagram of the example components on
the server side of the distributed proxy and cache system.
[0010] FIG. 1F illustrates an example diagram showing data flows
between example client side components in a distributed proxy and
cache system.
[0011] FIG. 2A depicts a block diagram illustrating an example of
client-side components in a distributed proxy and cache system
residing on a mobile device (e.g., wireless device) that manages
traffic in a wireless network (or broadband network) for resource
conservation, content caching, and/or traffic management. The
client-side proxy (or local proxy) can further categorize mobile
traffic and/or implement delivery policies based on application
behavior, content priority, user activity, and/or user
expectations, for example, for further use in facilitating aligned
data transfer to optimize connections established at the mobile
device.
[0012] FIG. 2B depicts a block diagram illustrating a further
example of components in the cache system shown in the example of
FIG. 2A which is capable of caching and adapting caching strategies
for mobile application behavior and/or network conditions.
Components capable of detecting long poll requests and managing
caching of long polls are also illustrated.
[0013] FIG. 2C depicts a block diagram illustrating additional
components in the application behavior detector and the caching
policy manager in the cache system shown in the example of FIG. 2A
which is further capable of detecting cache defeat and perform
caching of content addressed by identifiers intended to defeat
cache.
[0014] FIG. 2D depicts a block diagram illustrating examples of
additional components in the local cache shown in the example of
FIG. 2A which is further capable of performing mobile traffic
categorization and policy implementation based on application
behavior and/or user activity.
[0015] FIG. 2E depicts a block diagram illustrating examples of
additional components in the traffic shaping engine and the
application behavior detector shown in the example of FIG. 2A which
are further capable of facilitating alignment of incoming data
transfer to a mobile or broadband device, or its user, to optimize
the number of connections that need to be established for receiving
data over the wireless network or broadband network.
[0016] FIG. 3A depicts a block diagram illustrating an example of
server-side components in a distributed proxy and cache system that
manages traffic in a wireless network (or broadband network) for
resource conservation, content caching, and/or traffic management.
The server-side proxy (or proxy server) can further categorize
mobile traffic and/or implement delivery policies based on
application behavior, content priority, user activity, and/or user
expectations, for example, for further use in aligning data
transfer to optimize connections established for wireless
transmission to a mobile device.
[0017] FIG. 3B depicts a block diagram illustrating a further
example of components in the caching policy manager in the cache
system shown in the example of FIG. 3A which is capable of caching
and adapting caching strategies for mobile application behavior
and/or network conditions. Components capable of detecting long
poll requests and managing caching of long polls are also
illustrated.
[0018] FIG. 3C depicts a block diagram illustrating another example
of components in the proxy system shown in the example of FIG. 3A
which is further capable of managing and detecting cache defeating
mechanisms and monitoring content sources.
[0019] FIG. 3D depicts a block diagram illustrating examples of
additional components in proxy server shown in the example of FIG.
3A which is further capable of performing mobile traffic
categorization and policy implementation based on application
behavior and/or traffic priority.
[0020] FIG. 3E depicts a block diagram illustrating examples of
additional components in the traffic shaping engine of the example
of FIG. 3A which is further capable of aligning data transfer to a
mobile or broadband device, or other recipient, to optimize
connections established for transmission in a wireless network or
broadband network.
[0021] FIG. 4 depicts a flow diagram illustrating an example
process for distributed content caching between a mobile device
(e.g., any wireless device) and remote proxy and the distributed
management of content caching.
[0022] FIG. 5 depicts a timing diagram showing how data requests
from a mobile device (e.g., any wireless device) to an application
server/content provider in a wireless network (or broadband
network) can be coordinated by a distributed proxy system in a
manner such that network and battery resources are conserved
through using content caching and monitoring performed by the
distributed proxy system.
[0023] FIG. 6 depicts a table showing examples of different traffic
or application category types which can be used in implementing
network access and content delivery policies.
[0024] FIG. 7 depicts a table showing examples of different content
category types which can be used in implementing network access and
content delivery policies.
[0025] FIG. 8 depicts an interaction diagram showing how polls
having data requests from a mobile device (e.g., any wireless
device) to an application server/content provider over a wireless
network (or broadband network) can be can be cached on the local
proxy and managed by the distributed caching system.
[0026] FIG. 9 depicts a flow diagram illustrating an example
process for modeling signaling of a mobile device (e.g., any
wireless device) in a mobile network.
[0027] FIG. 10 depicts another flow diagram illustrating an example
process for modeling signaling of a mobile device (e.g., any
wireless device) in a mobile network.
[0028] FIG. 11A-FIG. 16D depict example cyclic redundancy codes
field calculations for use in determining general connection and
time calculations.
[0029] FIGS. 17A and 17B illustrate an example of calculating
connection flags and connection time intervals and an example radio
up interval, respectively.
[0030] FIG. 18 depicts an example scheme illustrating logs over a
period of time.
[0031] FIGS. 19A and 19B graphically illustrates a long poll
procedure for splitting one netlog item into two netlog items and
the conditions which must be true in order for the netlog to be
split in two parts, respectively.
[0032] FIGS. 20 and 21 graphically illustrate examples calculations
of the TIME_ON_NOT_CHARGING field and the TIME_ON_NOT_CHARGING
fields, respectively.
[0033] FIG. 22 depicts example measurement points from which a
analysis core module can perform measurements for modeling signals
in a data network.
[0034] FIGS. 23A-23E respectively depict graphics illustrations of
the output metrics which can be used in various embodiments of the
analysis core module.
[0035] FIGS. 24A-24J graphically illustrate various calculations of
example output metrics that can be used in embodiments of the
analysis core module.
[0036] FIG. 25 depicts an example diagram illustrating a general
architectural overview of a distributed Open Channel system
including the measurement points from which a analysis core module
can perform measurements for modeling signals in the data
network.
[0037] FIGS. 26A-26N show additional examples of and/or alternative
output metrics that the analysis core module can adapt.
[0038] FIG. 27 shows a diagrammatic representation of a machine in
the example form of a computer system within which a set of
instructions, for causing the machine to perform any one or more of
the methodologies discussed herein, may be executed.
DETAILED DESCRIPTION
[0039] The following description and drawings are illustrative and
are not to be construed as limiting. Numerous specific details are
described to provide a thorough understanding of the disclosure.
However, in certain instances, well-known or conventional details
are not described in order to avoid obscuring the description.
References to "one embodiment" or "an embodiment" in the present
disclosure can be, but not necessarily are, references to the same
embodiment and such references mean at least one of the
embodiments.
[0040] Reference in this specification to "one embodiment" or "an
embodiment" means that a particular feature, structure, or
characteristic described in connection with the embodiment is
included in at least one embodiment of the disclosure. The
appearances of the phrase "in one embodiment" in various places in
the specification are not necessarily all referring to the same
embodiment, nor are separate or alternative embodiments mutually
exclusive of other embodiments. Moreover, various features are
described which may be exhibited by some embodiments and not by
others. Similarly, various requirements are described which may be
requirements for some embodiments but not other embodiments.
[0041] The terms used in this specification generally have their
ordinary meanings in the art, within the context of the disclosure,
and in the specific context where each term is used. Certain terms
that are used to describe the disclosure are discussed below, or
elsewhere in the specification, to provide additional guidance to
the practitioner regarding the description of the disclosure. For
convenience, certain terms may be highlighted, for example using
italics and/or quotation marks. The use of highlighting has no
influence on the scope and meaning of a term; the scope and meaning
of a term is the same, in the same context, whether or not it is
highlighted. It will be appreciated that same thing can be said in
more than one way.
[0042] Consequently, alternative language and synonyms may be used
for any one or more of the terms discussed herein, nor is any
special significance to be placed upon whether or not a term is
elaborated or discussed herein. Synonyms for certain terms are
provided. A recital of one or more synonyms does not exclude the
use of other synonyms. The use of examples anywhere in this
specification, including examples of any terms discussed herein, is
illustrative only, and is not intended to further limit the scope
and meaning of the disclosure or of any exemplified term. Likewise,
the disclosure is not limited to various embodiments given in this
specification.
[0043] Without intent to limit the scope of the disclosure,
examples of instruments, apparatus, methods and their related
results according to the embodiments of the present disclosure are
given below. Note that titles or subtitles may be used in the
examples for convenience of a reader, which in no way should limit
the scope of the disclosure. Unless otherwise defined, all
technical and scientific terms used herein have the same meaning as
commonly understood by one of ordinary skill in the art to which
this disclosure pertains. In the case of conflict, the present
document, including definitions, will control.
[0044] The disclosed technology includes systems and methods for
modeling signaling and/or connections in a mobile network, and
specifically, the benefits of any optimization technique on the
traffic including signals and/or connections in the mobile network.
Embodiments can allocate signaling to specific applications (e.g.,
to determine which applications are chatty and which can cause
problematic signaling), and/or to further model the optimizations
or savings utilizing the disclosed traffic optimization
technology.
[0045] In some embodiments, the disclosed technology recognizes
that signaling in the mobile network can occur when, for example,
radio connections get set up (e.g., connected) or torn down (e.g.,
disconnected). Each radio connection can be used for one or more
transactions/data transfers, which can source from one or more
applications. The disclosed technology defines whether a
transaction causes a connection (and thus signaling), and can
further model, compute, or otherwise quantify the signaling or
connection savings resulting from any traffic optimization
techniques utilized in the signaling or data path.
[0046] In some embodiments, to enable or enhance the performance of
the data traffic and signal optimization for the network, the
disclosed technology includes one or more cyclic redundancy codes
fields (e.g., an expanded fields) that are calculated by, for
example, a analysis core module, to define and identify at least:
(1) whether a transaction causes a connection (and thus signaling);
and (2) the number of connections that are reduced or saved by the
disclosed embodiments of distributed caching and proxy system.
[0047] FIG. 1A illustrates an example diagram of a system where a
host server 100 facilitates management of traffic, content caching,
and/or resource conservation between mobile devices (e.g., wireless
devices 150 or client devices 150), and an application server or
content provider 110, or other servers such as an ad server 120A,
promotional content server 120B, or an e-coupon server 120C in a
wireless network (or broadband network) for resource conservation.
The host server 100 can further become aware of mobile device radio
states for use in selecting a suitable communications channel for
sending messages generated by the host server or other control
signals and facilitate using a user as an end point for profiling
and optimizing the delivery of content and data in a wireless
network.
[0048] The mobile/client devices 150 can be any system and/or
device, and/or any combination of devices/systems that is able to
establish a connection, including wired, wireless, cellular
connections with another device, a server and/or other systems such
as host server 100 and/or application server/content provider 110.
Client/mobile devices 150 will typically include a display and/or
other output functionalities to present information and data
exchanged between among the devices 150 and/or the host server 100
and/or application server/content provider 110. The application
server/content provider 110 can by any server including third party
servers or service/content providers further including
advertisement, promotional content, publication, or electronic
coupon servers or services. Similarly, separate advertisement
servers 120A, promotional content servers 120B, and/or e-Coupon
servers 120C as application servers or content providers are
illustrated by way of example.
[0049] For example, the client/mobile devices 150 can include
mobile, hand held or portable devices, wireless devices, or
non-portable devices and can be any of, but not limited to, a
server desktop, a desktop computer, a computer cluster, or portable
devices, including a notebook, a laptop computer, a handheld
computer, a palmtop computer, a mobile phone, a cell phone, a smart
phone, a PDA, a Blackberry device, a Palm device, any tablet, a
phablet (a class of smart phones with larger screen sizes between a
typical smart phone and tablet), a handheld tablet (e.g., an iPad,
the Galaxy series, the Nexus, the Kindles, Kindle Fires, any
Android-based tablet, Windows-based tablet, Amazon-based, or any
other tablet), any portable readers/reading devices, a hand held
console, a hand held gaming device or console, a head mounted
device, a head mounted display, a thin client or any Super Phone
such as the iPhone, and/or any other portable, mobile, hand held
devices, or fixed wireless interface such as a M2M device, etc. In
one embodiment, the client devices 150 (or mobile devices 150),
host server 100, and application server 110 are coupled via a
network 106 and/or a network 108. In some embodiments, the devices
150 and host server 100 may be directly connected to one
another.
[0050] The input mechanism on client devices 150 can include touch
screen keypad (including single touch, multi-touch, gesture sensing
in 2D or 3D, etc.), a physical keypad, a mouse, a pointer, a track
pad, a stylus, a stylus detector/sensor/receptor, motion
detector/sensor (e.g., including 1-axis, 2-axis, 3-axis
accelerometer, etc.), a face detector/recognizer, a retinal
detector/scanner, a light sensor, capacitance sensor, resistance
sensor, temperature sensor, proximity sensor, a piezoelectric
device, device orientation detector (e.g., electronic compass, tilt
sensor, rotation sensor, gyroscope, accelerometer), or any
combination of the above.
[0051] Signals received or detected indicating user activity at
client devices 150 through one or more of the above input
mechanism, or others, can be used in the disclosed technology in
acquiring context awareness at the client device 150. Context
awareness at client devices 150 generally includes, by way of
example but not limitation, client device 150 operation or state
acknowledgement, management, user activity/behavior/interaction
awareness, detection, sensing, tracking, trending, and/or
application (e.g., mobile applications) type, behavior, activity,
operating state, etc.
[0052] Context awareness in the present disclosure also includes
knowledge and detection of network side contextual data and can
include network information such as network capacity, bandwidth,
traffic, type of network/connectivity, and/or any other operational
state data. Network side contextual data can be received from
and/or queried from network service providers (e.g., cell provider
112 and/or Internet service providers) of the network 106 and/or
network 108 (e.g., by the host server and/or devices 150). In
addition to application context awareness as determined from the
client 150 side, the application context awareness may also be
received from or obtained/queried from the respective
application/service providers 110 (by the host 100 and/or client
devices 150).
[0053] The host server 100 can use, for example, contextual
information obtained for client devices 150, networks 106/108,
applications (e.g., mobile applications), application
server/provider 110, or any combination of the above, to manage the
traffic in the system to satisfy data needs of the client devices
150 (e.g., to satisfy application or any other request including
HTTP request). In one embodiment, the traffic is managed by the
host server 100 to satisfy data requests made in response to
explicit or non-explicit user 103 requests and/or
device/application maintenance tasks. The traffic can be managed
such that network consumption, for example, use of the cellular
network is conserved for effective and efficient bandwidth
utilization. In addition, the host server 100 can manage and
coordinate such traffic in the system such that use of device 150
side resources (e.g., including but not limited to battery power
consumption, radio use, processor/memory use) are optimized with a
general philosophy for resource conservation while still optimizing
performance and user experience.
[0054] For example, in context of battery conservation, the device
150 can observe user activity (for example, by observing user
keystrokes, backlight status, or other signals via one or more
input mechanisms, etc.) and alters device 150 behaviors. The device
150 can also request the host server 100 to alter the behavior for
network resource consumption based on user activity or
behavior.
[0055] In one embodiment, the traffic management for resource
conservation is performed using a distributed system between the
host server 100 and client device 150. The distributed system can
include proxy server and cache components on the server side 100
and on the device/client side, for example, as shown by the server
cache 135 on the server 100 side and the local cache 185 on the
client 150 side.
[0056] Functions and techniques disclosed for context aware traffic
management for resource conservation in networks (e.g., network 106
and/or 108) and devices 150, reside in a distributed proxy and/or
cache system (e.g., (distributed) traffic optimizer, traffic
management system, (distributed) content caching mechanism for
traffic alleviation) (e.g., (distributed) traffic optimizer,
traffic management system, (distributed) content caching mechanism
for traffic alleviation). The proxy and cache system can be
distributed between, and reside on, a given client device 150 in
part or in whole and/or host server 100 in part or in whole. The
distributed proxy and/or cache system (e.g., (distributed) traffic
optimizer, traffic management system, (distributed) content caching
mechanism for traffic alleviation) (e.g., (distributed) traffic
optimizer, traffic management system, (distributed) content caching
mechanism for traffic alleviation) are illustrated with further
reference to the example diagram shown in FIG. 1C. Functions and
techniques performed by the (distributed) proxy and/or cache
components in the client device 150, the host server 100, and the
related components therein are described, respectively, in detail
with further reference to the examples of FIG. 2-5.
[0057] In one embodiment, client devices 150 communicate with the
host server 100 and/or the application server 110 over network 106,
which can be a cellular network and/or a broadband network. To
facilitate overall traffic management between devices 150 and
various application servers/content providers 110 to implement
network (bandwidth utilization) and device resource (e.g., battery
consumption), the host server 100 can communicate with the
application server/providers 110 over the network 108, which can
include the Internet (e.g., a broadband network).
[0058] In general, the networks 106 and/or 108, over which the
client devices 150, the host server 100, and/or application server
110 communicate, may be a cellular network, a broadband network, a
telephonic network, an open network, such as the Internet, or a
private network, such as an intranet and/or the extranet, or any
combination thereof. For example, the Internet can provide file
transfer, remote log in, email, news, RSS, cloud-based services,
instant messaging, visual voicemail, push mail, VoIP, and other
services through any known or convenient protocol, such as, but is
not limited to the TCP/IP protocol, UDP, HTTP, DNS, FTP, UPnP, NSF,
ISDN, PDH, RS-232, SDH, SONET, etc.
[0059] The networks 106 and/or 108 can be any collection of
distinct networks operating wholly or partially in conjunction to
provide connectivity to the client devices 150 and the host server
100 and may appear as one or more networks to the serviced systems
and devices. In one embodiment, communications to and from the
client devices 150 can be achieved by, an open network, such as the
Internet, or a private network, broadband network, such as an
intranet and/or the extranet. In one embodiment, communications can
be achieved by a secure communications protocol, such as secure
sockets layer (SSL), or transport layer security (TLS).
[0060] In addition, communications can be achieved via one or more
networks, such as, but are not limited to, one or more of WiMax, a
Local Area Network (LAN), Wireless Local Area Network (WLAN), a
Personal area network (PAN), a Campus area network (CAN), a
Metropolitan area network (MAN), a Wide area network (WAN), a
Wireless wide area network (WWAN), or any broadband network, and
further enabled with technologies such as, by way of example,
Global System for Mobile Communications (GSM), Personal
Communications Service (PCS), Bluetooth, WiFi, Fixed Wireless Data,
2G, 2.5G, 3G (e.g., WCDMA/UMTS based 3G networks), 4G,
IMT-Advanced, pre-4G, LTE Advanced, mobile WiMax, WiMax 2,
WirelessMAN-Advanced networks, enhanced data rates for GSM
evolution (EDGE), General packet radio service (GPRS), enhanced
GPRS, iBurst, UMTS, HSPDA, HSUPA, HSPA, HSPA+, UMTS-TDD,
1.times.RTT, EV-DO, messaging protocols such as, TCP/IP, SMS, MMS,
extensible messaging and presence protocol (XMPP), real time
messaging protocol (RTMP), instant messaging and presence protocol
(IMPP), instant messaging, USSD, IRC, or any other wireless data
networks, broadband networks, or messaging protocols.
[0061] With more detailed description below, and with particular
reference to FIGS. 2A-2E and 3A-3E, one or more embodiments
disclosed herein can provide techniques to model the signaling that
takes place in a mobile network (e.g., network 106), to allocate
signaling to one or more specific applications (e.g., so as to
determine which applications are causing the traffic signals), and
to model traffic signaling savings resulted from the distributed
caching and proxy system described herein (e.g., as implemented by
client-side proxy 175 and/or server-side proxy 125, FIG. 1C).
[0062] The present embodiments recognize that data signaling in the
mobile network takes place when, for example, radio connections get
set up (e.g., connected) or torn down (e.g., disconnected).
Moreover, each radio connection can be used for one or more
transactions/data transfers, which can source from one or more
applications.
[0063] To enable or enhance the performance of the data traffic and
signal optimization for the network, the present embodiments can
include one or more fields (e.g., expanded fields). The one or more
fields can be calculated by, for example, the client-side proxy 175
and/or server-side proxy 125, to define and identify at least: (1)
whether a transaction causes a connection (and thus corresponding
signaling); and (2) the number of connections that are reduced or
saved by the disclosed embodiments of distributed caching and proxy
system.
[0064] It is noted that, for convenience, a client (e.g., local
proxy 105, 175, 275) of the distributed caching system can be
referred to herein as an "Open Channel client" or "OC client."
Similarly, a server (e.g., host server 111, 100, 300 hosting proxy
server 113, 125, 325) of the distributed caching system can be
referred to herein as an "Open Channel server" or "OC server." The
client and/or server, individually or collectively, can implement
the distributed caching techniques described herein. The
distributed caching techniques include, but are not limited to, the
Signal Optimization and Extended Caching techniques referred to
herein as "Open Channel" or "OC."
[0065] In one embodiment, a analysis core module can perform
calculations and/or determinations for measurements and modeling of
the signals. The analysis core module, which can be included in
client-side proxy 175 and/or server-side proxy 125 (e.g., as shown
in FIGS. 2E and 3E), is described in more detail below.
[0066] FIG. 1A-1 depicts an example block diagram illustrating an
architectural overview of a distributed Open Channel system
including an Open Channel (OC) client (or local) proxy 175 and an
OC (or host) server 100 that are configured to, individually or in
combination, model signaling in a mobile network as described
herein.
[0067] In one embodiment, a analysis core tool or module (not
shown) can calculate expanded fields that are maintained and
utilized by the analysis core tool to model signaling of a mobile
device in a mobile network. More specifically, the analysis core
tool can model the effects of the Open Channel architecture (e.g.,
the distributed caching techniques including the Signal
Optimization and Extended Caching techniques discussed herein). The
analysis core tool or module can include hardware and/or software
modules and can be included in one or both of the OC client (local)
proxy 175 and an OC (host) server 150.
[0068] In one embodiment, the expanded fields are calculated in
order to model the optimizations or savings of the Open Channel
architecture (e.g., the mobile data traffic optimization
technology). For example the expanded fields can measure an overall
efficiency for the Open Channel architecture. The fields can be
calculated by the OC client (local) proxy 175 and/or by the OC
(host) server 150. Additionally, fields can be calculated per
mobile device and/or fields can be calculated for modeling the
signaling attributed to individual applications executing on a
mobile device. For example, the signaling can be identified and
allocated (or attributed) to specific applications to, for example,
determine which applications are chatty, which applications are
causing problematic signaling, etc.
[0069] The mobile device 150 can include any number of mobile
device applications. The applications can be built-in,
pre-installed, or download by a user of the mobile device.
Additionally, the applications can be in communication with (be
handled by) the OC client proxy 175 or have a direct connection to
the network (e.g., Internet). As illustrated in the example of FIG.
1A-1, applications 1-3 are shown each initiating transactions.
Applications 1 and 2 are shown being handled by the OC client 175
while application 3 is shown having a direct connection to the
network (e.g., Internet). Applications 1 and 2 may also be referred
to as "radio-aware" herein. Application 3 is not handled by Open
Channel architecture, but nevertheless can cause radio up (i.e.,
mobile device radio connection). The radio connection can be
tracked using a radio log. It is appreciated that each application
can initiate any number of transactions that may or may not cause
network signaling.
[0070] As discussed above, expanded fields described herein can be
calculated in order to measure Open Channel solution efficiency
including signaling efficiency and time connected efficiency. For
example, the signaling efficiency and time connected efficiency can
be calculated for the signaling associated with a mobile device.
The signaling efficiency (also referred to as signaling savings)
represents an amount of saved mobile network connections.
Similarly, the time connected efficiency (also referred to as time
savings) represents amount of saved mobile network up-time.
[0071] In one embodiment, the expanded fields can be divided into
multiple types. For example, the expanded fields can include a
connection flag type and a time connected counts type.
Additionally, the expanded fields can be divided into several
categories as illustrated below in Table 1.
TABLE-US-00001 TABLE 1 fields categories Actual Simulated Simulated
per App Simulated per Host Actual A RS RSpA RSpH Virtual V VS VSpA
VSpH Savings V - A VS - RS VSpA - RSpA VSpH - RSpH
[0072] As discussed above, a analysis core tool or module (not
shown) can calculate expanded fields that are maintained and
utilized by the analysis core tool to model signaling of a mobile
device in a mobile network. In one embodiment, modeling the
signaling of the mobile device includes making various connection
and time calculations. Examples of the various connection and time
calculations are discussed in greater detail with respect to FIGS.
10A-26N.
[0073] FIG. 1B illustrates an example diagram of a proxy and cache
system distributed between the host server 100 and device 150 which
facilitates network traffic management between the device 150 and
an application server or content provider 110, or other servers
such as an ad server 120A, promotional content server 120B, or an
e-coupon server 120C for resource conservation and content caching.
The proxy system distributed among the host server 100 and the
device 150 can further monitor mobile application activities for
malicious traffic on a mobile device and/or automatically generate
and/or distribute policy information regarding malicious traffic in
a wireless network.
[0074] The distributed proxy and/or cache system (e.g.,
(distributed) traffic optimizer, traffic management system,
(distributed) content caching mechanism for traffic alleviation)
(e.g., (distributed) traffic optimizer, traffic management system,
(distributed) content caching mechanism for traffic alleviation)
can include, for example, the proxy server 125 (e.g., remote proxy)
and the server cache, 135 components on the server side. The
server-side proxy 125 and cache 135 can, as illustrated, reside
internal to the host server 100. In addition, the proxy server 125
and cache 135 on the server-side can be partially or wholly
external to the host server 100 and in communication via one or
more of the networks 106 and 108. For example, the proxy server 125
may be external to the host server and the server cache 135 may be
maintained at the host server 100. Alternatively, the proxy server
125 may be within the host server 100 while the server cache is
external to the host server 100. In addition, each of the proxy
server 125 and the cache 135 may be partially internal to the host
server 100 and partially external to the host server 100. The
application server/content provider 110 can by any server including
third party servers or service/content providers further including
advertisement, promotional content, publication, or electronic
coupon servers or services. Similarly, separate advertisement
servers 120A, promotional content servers 120B, and/or e-Coupon
servers 120C as application servers or content providers are
illustrated by way of example.
[0075] The distributed system can also, include, in one embodiment,
client-side components, including by way of example but not
limitation, a local proxy 175 (e.g., a mobile client on a mobile
device) and/or a local cache 185, which can, as illustrated, reside
internal to the device 150 (e.g., a mobile device).
[0076] In addition, the client-side proxy 175 and local cache 185
can be partially or wholly external to the device 150 and in
communication via one or more of the networks 106 and 108. For
example, the local proxy 175 may be external to the device 150 and
the local cache 185 may be maintained at the device 150.
Alternatively, the local proxy 175 may be within the device 150
while the local cache 185 is external to the device 150. In
addition, each of the proxy 175 and the cache 185 may be partially
internal to the host server 100 and partially external to the host
server 100.
[0077] In one embodiment, the distributed system can include an
optional caching proxy server 199. The caching proxy server 199 can
be a component which is operated by the application server/content
provider 110, the host server 100, or a network service provider
112, and or any combination of the above to facilitate network
traffic management for network and device resource conservation.
Proxy server 199 can be used, for example, for caching content to
be provided to the device 150, for example, from one or more of,
the application server/provider 110, host server 100, and/or a
network service provider 112. Content caching can also be entirely
or partially performed by the remote proxy 125 to satisfy
application requests or other data requests at the device 150.
[0078] In context aware traffic management and optimization for
resource conservation in a network (e.g., cellular or other
wireless networks), characteristics of user activity/behavior
and/or application behavior at a mobile device (e.g., any wireless
device) 150 can be tracked by the local proxy 175 and communicated,
over the network 106 to the proxy server 125 component in the host
server 100, for example, as connection metadata. The proxy server
125 which in turn is coupled to the application server/provider 110
provides content and data to satisfy requests made at the device
150.
[0079] In addition, the local proxy 175 can identify and retrieve
mobile device properties, including one or more of, battery level,
network that the device is registered on, radio state, or whether
the mobile device is being used (e.g., interacted with by a user).
In some instances, the local proxy 175 can delay, expedite
(prefetch), and/or modify data prior to transmission to the proxy
server 125, when appropriate, as will be further detailed with
references to the description associated with the examples of FIG.
2-5.
[0080] The local database 185 can be included in the local proxy
175 or coupled to the local proxy 175 and can be queried for a
locally stored response to the data request prior to the data
request being forwarded on to the proxy server 125. Locally cached
responses can be used by the local proxy 175 to satisfy certain
application requests of the mobile device 150, by retrieving cached
content stored in the cache storage 185, when the cached content is
still valid.
[0081] Similarly, the proxy server 125 of the host server 100 can
also delay, expedite, or modify data from the local proxy prior to
transmission to the content sources (e.g., the application
server/content provider 110). In addition, the proxy server 125
uses device properties and connection metadata to generate rules
for satisfying request of applications on the mobile device 150.
The proxy server 125 can gather real time traffic information about
requests of applications for later use in optimizing similar
connections with the mobile device 150 or other mobile devices.
[0082] In general, the local proxy 175 and the proxy server 125 are
transparent to the multiple applications executing on the mobile
device. The local proxy 175 is generally transparent to the
operating system or platform of the mobile device and may or may
not be specific to device manufacturers. In some instances, the
local proxy 175 is optionally customizable in part or in whole to
be device specific. In some embodiments, the local proxy 175 may be
bundled into a wireless model, a firewall, and/or a router.
[0083] In one embodiment, the host server 100 can in some
instances, utilize the store and forward functions of a short
message service center (SMSC) 112, such as that provided by the
network service provider, in communicating with the device 150 in
achieving network traffic management. Note that 112 can also
utilize any other type of alternative channel including USSD or
other network control mechanisms. The host server 100 can forward
content or HTTP responses to the SMSC 112 such that it is
automatically forwarded to the device 150 if available, and for
subsequent forwarding if the device 150 is not currently
available.
[0084] In general, the disclosed distributed proxy and/or cache
system (e.g., (distributed) traffic optimizer, traffic management
system, (distributed) content caching mechanism for traffic
alleviation) (e.g., (distributed) traffic optimizer, traffic
management system, (distributed) content caching mechanism for
traffic alleviation) allows optimization of network usage, for
example, by serving requests from the local cache 185, the local
proxy 175 reduces the number of requests that need to be satisfied
over the network 106. Further, the local proxy 175 and the proxy
server 125 may filter irrelevant data from the communicated data.
In addition, the local proxy 175 and the proxy server 125 can also
accumulate low priority data and send it in batches to avoid the
protocol overhead of sending individual data fragments. The local
proxy 175 and the proxy server 125 can also compress or transcode
the traffic, reducing the amount of data sent over the network 106
and/or 108. The signaling traffic in the network 106 and/or 108 can
be reduced, as the networks are now used less often and the network
traffic can be synchronized among individual applications.
[0085] With respect to the battery life of the mobile device 150,
by serving application or content requests from the local cache
185, the local proxy 175 can reduce the number of times the radio
module is powered up. The local proxy 175 and the proxy server 125
can work in conjunction to accumulate low priority data and send it
in batches to reduce the number of times and/or amount of time when
the radio is powered up. The local proxy 175 can synchronize the
network use by performing the batched data transfer for all
connections simultaneously.
[0086] FIG. 1C illustrates an example diagram of the logical
architecture of a distributed proxy and cache system.
[0087] The distributed system can include, for example the
following components:
[0088] Client Side Proxy 175: a component installed in the
Smartphone, mobile device or wireless device 150 that interfaces
with device's operating system, as well as with data services and
applications installed in the device. The client side proxy 175 is
typically compliant with and able to operate with standard or state
of the art networking protocols. Additional components and features
of the client-side proxy 175 are illustrated with further
references to the examples of FIG. 2A-FIG. 2B and FIG. 4A-4C.
[0089] The server side proxy 125 can include one or more servers
that can interface with third party application servers (e.g.,
199), mobile operator's network (which can be proxy 199 or an
additional server that is not illustrated) and/or the client side
proxy 175. In general, the server side proxy 125 can be compliant
with and is generally able to operate with standard or state of the
art networking protocols and/or specifications for interacting with
mobile network elements and/or third party servers. Additional
components and features of the server-side proxy 125 are
illustrated with further references to the examples of FIG. 3A-FIG.
3B and FIG. 5A-5C.
[0090] Reporting and Usage Analytics Server 174: The Reporting and
Usage Analytics system or component 174 can collect information
from the client side 175 and/or the server side 125 and provides
the necessary tools for producing reports and usage analytics can
used for analyzing traffic and signaling data. Such analytics can
be used by the proxy system in managing/reducing network traffic or
by the network operator in monitoring their networks for possible
improvements and enhancements. Note that the reporting and usage
analytics system/component 174 as illustrated, may be a server
separate from the server-side proxy 125, or it may be a component
of the server-side proxy 125, residing partially or wholly
therein.
[0091] FIG. 1D illustrates an example diagram showing the
architecture of client side components in a distributed proxy and
cache system.
[0092] The client side components 175 can include software
components or agents installed on the mobile device that enables
traffic optimization and performs the related functionalities on
the client side. Components of the client side proxy 175 can
operate transparently for end users and applications 163. The
client side proxy 175 can be installed on mobile devices for
optimization to take place, and it can effectuate changes on the
data routes. Once data routing is modified, the client side proxy
175 can respond to application requests to service providers or
host servers, in addition to or instead of letting those
applications 163 access data network directly. In general,
applications 163 on the mobile device will not notice that the
client side proxy 175 is responding to their requests. Some example
components of the client side proxy 175 are described as
follows:
[0093] Device State Monitor 121: The device state monitor 121 can
be responsible for identifying several states and metrics in the
device, such as network status, display status, battery level, etc.
such that the remaining components in the client side proxy 175 can
operate and make decisions according to device state, acting in an
optimal way in each state.
[0094] Traffic Recognizer 122: The traffic recognizer 122 analyzes
all traffic between the wireless device applications 163 and their
respective host servers in order to identify recurrent patterns.
Supported transport protocols include, for example, DNS, HTTP and
HTTPS, such that traffic through those ports is directed to the
client side proxy 175. While analyzing traffic, the client side
proxy 175 can identify recurring polling patterns which can be
candidates to be performed remotely by the server side proxy 125,
and send to the protocol optimizer 123.
[0095] Protocol Optimizer 123: The protocol optimizer 123 can
implement the logic of serving recurrent request from the local
cache 185 instead of allowing those request go over the network to
the service provider/application host server. One is its tasks is
to eliminate or minimize the need to send requests to the network,
positively affecting network congestion and device battery
life.
[0096] Local Cache 185: The local cache 185 can store responses to
recurrent requests, and can be used by the Protocol Optimizer 123
to send responses to the applications 163.
[0097] Traffic Scheduler 124: The traffic scheduler 124 can
temporally move communications to optimize usage of device
resources by unifying keep-alive signaling so that some or all of
the different applications 163 can send keep-alive messages at the
same time (traffic pipelining) Traffic scheduler 124 may also
decide to delay transmission of data that is not relevant at a
given time (for example, when the device is not actively used).
[0098] Policy Manager 125: The policy manager 125 can store and
enforce traffic optimization and reporting policies provisioned by
a Policy Management Server (PMS). At the client side proxy 175
first start, traffic optimization and reporting policies (policy
profiles) that is to be enforced in a particular device can be
provisioned by the Policy Management Server.
[0099] Watch Dog 127: The watch dog 127 can monitor the client side
proxy 175 operating availability. In case the client side proxy 175
is not working due to a failure or because it has been disabled,
the watchdog 127 can reset DNS routing rules information and can
restore original DNS settings for the device to continue working
until the client side proxy 175 service is restored.
[0100] Reporting Agent 126: The reporting agent 126 can gather
information about the events taking place in the device and sends
the information to the Reporting Server. Event details are stored
temporarily in the device and transferred to reporting server only
when the data channel state is active. If the client side proxy 175
doesn't send records within twenty-four hours, the reporting agent
126 may attempt to open the connection and send recorded entries
or, in case there are no entries in storage, an empty reporting
packet. All reporting settings are configured in the policy
management server.
[0101] Push Client 128: The push client 128 can be responsible for
the traffic to between the server side proxy 125 and the client
side proxy 175. The push client 128 can send out service requests
like content update requests and policy update requests, and
receives updates to those requests from the server side proxy 125.
In addition, push client 128 can send data to a reporting server
(e.g., the reporting and/or usage analytics system which may be
internal to or external to the server side proxy 125).
[0102] The proxy server 199 has a wide variety of uses, from
speeding up a web server by caching repeated requests, to caching
web, DNS and other network lookups for a group of clients sharing
network resources. The proxy server 199 is optional. The
distributed proxy and cache system (125 and/or 175) allows for a
flexible proxy configuration using either the proxy 199, additional
proxy(s) in operator's network, or integrating both proxies 199 and
an operator's or other third-party's proxy.
[0103] FIG. 1E illustrates a diagram of the example components on
the server side of the distributed proxy and cache system.
[0104] The server side 125 of the distributed system can include,
for example a relay server 142, which interacts with a traffic
harmonizer 144, a polling server 145 and/or a policy management
server 143. Each of the various components can communicate with the
client side proxy 175, or other third party (e.g., application
server/service provider 110 and/or other proxy 199) and/or a
reporting and usage analytics system. Some example components of
the server side proxy 125 is described as follows:
[0105] Relay Server 142: The relay server 142 is the routing agent
in the distributed proxy architecture. The relay server 142 manages
connections and communications with components on the client-side
proxy 175 installed on devices and provides an administrative
interface for reports, provisioning, platform setup, and so on.
[0106] Notification Server 141: The notification server 141 is a
module able to connect to an operator's SMSC gateways and deliver
SMS notifications to the client-side proxy 175. SMS notifications
can be used when an IP link is not currently active, in order to
avoid the client-side proxy 175 from activating a connection over
the wireless data channel, thus avoiding additional signaling
traffic. However, if the IP connection happens to be open for some
other traffic, the notification server 141 can use it for sending
the notifications to the client-side proxy 175. The user database
can store operational data including endpoint (MSISDN),
organization and Notification server 141 gateway for each resource
(URIs or URLs).
[0107] Traffic Harmonizer 144: The traffic harmonizer 144 can be
responsible for communication between the client-side proxy 175 and
the polling server 145. The traffic harmonizer 144 connects to the
polling server 145 directly or through the data storage 130, and to
the client over any open or proprietary protocol such as the 7TP,
implemented for traffic optimization. The traffic harmonizer 144
can be also responsible for traffic pipelining on the server side:
if there's cached content in the database for the same client, this
can be sent over to the client in one message.
[0108] Polling Server 145: The polling server 145 can poll third
party application servers on behalf of applications that are being
optimized). If a change occurs (i.e. new data available) for an
application, the polling server 145 can report to the traffic
harmonizer 144 which in turn sends a notification message to the
client-side proxy 175 for it to clear the cache and allow
application to poll application server directly.
[0109] Policy Management Server 143: The policy management server
(PMS) 143 allows administrators to configure and store policies for
the client-side proxies 175 (device clients). It also allows
administrators to notify the client-side proxies 175 about policy
changes. Using the policy management server 143, each operator can
configure the policies to work in the most efficient way for the
unique characteristics of each particular mobile operator's
network.
[0110] Reporting and Usage Analytics Component: The Reporting and
Usage Analytics component or system collects information from the
client side 175 and/or from the server side 125, and provides the
tools for producing reports and usage analytics that operators can
use for analyzing application signaling and data consumption.
[0111] FIG. 1F illustrates an example diagram showing data flows
between example client side components in a distributed proxy and
cache system. Traffic from applications (e.g., App1, App2, App3 to
AppN), client side proxy (e.g., local proxy) 175, IP Routing Tables
(e.g., in the Android Operating System Layer), Network Access Layer
and Wireless Network are depicted.
[0112] In one implementation, non-optimized application traffic
flow, such as traffic from App1, can completely bypass the client
side proxy 175 components and proceed directly through the
operating system layer (e.g., the Android OS layer) and Network
Access Layer to the wireless network. Traffic that that is not
optimized can include, but is not limited to: rich media, like
video and audio, as well as traffic from networks and applications
that has been configured to bypass optimization and traffic pending
optimization, and the like. In one embodiment, all traffic can be
configured to bypass the client side/server side proxy.
[0113] In another implementation, optimized application traffic,
such as traffic from App2, can be redirected from the application
to the client side proxy 175. By default, this can be traffic on
ports 80 (HTTP) and 53 (DNS), and selected traffic on port 443
(HTTPS), for example. However, traffic to other ports can be
configured to be directed to the client side proxy.
[0114] In yet another implementation, traffic flow can be between
the client side proxy 175 and the origin servers (e.g., content
server 110) via the Internet and/or between the client side proxy
175 and the server side proxy (e.g., proxy server) 125.
[0115] FIG. 2A depicts a block diagram illustrating an example of
client-side components in a distributed proxy and cache system
residing on a device 250 that manages traffic in a wireless network
for resource conservation, content caching, and/or traffic
management. The client-side proxy (or local proxy 275) can further
categorize mobile traffic and/or implement delivery policies based
on application behavior, content priority, user activity, and/or
user expectations.
[0116] The device 250, which can be a portable or mobile device
(e.g., any wireless device), such as a portable phone, generally
includes, for example, a network interface 208 an operating system
204, a context API 206, and mobile applications which may be
proxy-unaware 210 or proxy-aware 220. Note that the device 250 is
specifically illustrated in the example of FIG. 2 as a mobile
device, such is not a limitation and that device 250 may be any
wireless, broadband, portable/mobile or non-portable device able to
receive, transmit signals to satisfy data requests over a network
including wired or wireless networks (e.g., WiFi, cellular,
Bluetooth, LAN, WAN, etc.).
[0117] The network interface 208 can be a networking module that
enables the device 250 to mediate data in a network with an entity
that is external to the host server 250, through any known and/or
convenient communications protocol supported by the host and the
external entity. The network interface 208 can include one or more
of a network adaptor card, a wireless network interface card (e.g.,
SMS interface, WiFi interface, interfaces for various generations
of mobile communication standards including but not limited to 2G,
3G, 3.5G, 4G, LTE, etc.,), Bluetooth, or whether or not the
connection is via a router, an access point, a wireless router, a
switch, a multilayer switch, a protocol converter, a gateway, a
bridge, a bridge router, a hub, a digital media receiver, and/or a
repeater.
[0118] Device 250 can further include, client-side components of
the distributed proxy and cache system which can include, a local
proxy 275 (e.g., a mobile client of a mobile device) and a cache
285. In one embodiment, the local proxy 275 includes a user
activity module 215, a proxy API 225, a request/transaction manager
235, a caching policy manager 245 having an application protocol
module 248, a traffic shaping engine 255, and/or a connection
manager 265. The traffic shaping engine 255 may further include an
alignment module 256 and/or a batching module 257, the connection
manager 265 may further include a radio controller 266. The
request/transaction manager 235 can further include an application
behavior detector 236 and/or a prioritization engine 241, the
application behavior detector 236 may further include a pattern
detector 237 and/or and application profile generator 239.
Additional or less components/modules/engines can be included in
the local proxy 275 and each illustrated component.
[0119] As used herein, a "module," "a manager," a "handler," a
"detector," an "interface," a "controller," a "normalizer," a
"generator," an "invalidator," or an "engine" includes a general
purpose, dedicated or shared processor and, typically, firmware or
software modules that are executed by the processor. Depending upon
implementation-specific or other considerations, the module,
manager, handler, detector, interface, controller, normalizer,
generator, invalidator, or engine can be centralized or its
functionality distributed. The module, manager, handler, detector,
interface, controller, normalizer, generator, invalidator, or
engine can include general or special purpose hardware, firmware,
or software embodied in a computer-readable (storage) medium for
execution by the processor.
[0120] As used herein, a computer-readable medium or
computer-readable storage medium is intended to include all mediums
that are statutory (e.g., in the United States, under 35 U.S.C.
101), and to specifically exclude all mediums that are
non-statutory in nature to the extent that the exclusion is
necessary for a claim that includes the computer-readable (storage)
medium to be valid. Known statutory computer-readable mediums
include hardware (e.g., registers, random access memory (RAM),
non-volatile (NV) storage, to name a few), but may or may not be
limited to hardware.
[0121] In one embodiment, a portion of the distributed proxy and
cache system for network traffic management resides in or is in
communication with device 250, including local proxy 275 (mobile
client) and/or cache 285. The local proxy 275 can provide an
interface on the device 250 for users to access device applications
and services including email, IM, voice mail, visual voicemail,
feeds, Internet, games, productivity tools, or other applications,
etc.
[0122] The proxy 275 is generally application independent and can
be used by applications (e.g., both proxy-aware and proxy-unaware
applications 210 and 220 or mobile applications) to open TCP
connections to a remote server (e.g., the server 100 in the
examples of FIG. 1A-1B and/or server proxy 125/325 shown in the
examples of FIG. 1B and FIG. 3A). In some instances, the local
proxy 275 includes a proxy API 225 which can be optionally used to
interface with proxy-aware applications 220 (or applications (e.g.,
mobile applications) on a mobile device (e.g., any wireless
device)).
[0123] The applications 210 and 220 can generally include any user
application, widgets, software, HTTP-based application, web
browsers, video or other multimedia streaming or downloading
application, video games, social network applications, email
clients, RSS management applications, application stores, document
management applications, productivity enhancement applications,
etc. The applications can be provided with the device OS, by the
device manufacturer, by the network service provider, downloaded by
the user, or provided by others.
[0124] One embodiment of the local proxy 275 includes or is coupled
to a context API 206, as shown. The context API 206 may be a part
of the operating system 204 or device platform or independent of
the operating system 204, as illustrated. The operating system 204
can include any operating system including but not limited to, any
previous, current, and/or future versions/releases of, Windows
Mobile, iOS, Android, Symbian, Palm OS, Brew MP, Java 2 Micro
Edition (J2ME), Blackberry, etc.
[0125] The context API 206 may be a plug-in to the operating system
204 or a particular client/application on the device 250. The
context API 206 can detect signals indicative of user or device
activity, for example, sensing motion, gesture, device location,
changes in device location, device backlight, keystrokes, clicks,
activated touch screen, mouse click or detection of other pointer
devices. The context API 206 can be coupled to input devices or
sensors on the device 250 to identify these signals. Such signals
can generally include input received in response to explicit user
input at an input device/mechanism at the device 250 and/or
collected from ambient signals/contextual cues detected at or in
the vicinity of the device 250 (e.g., light, motion, piezoelectric,
etc.).
[0126] In one embodiment, the user activity module 215 interacts
with the context API 206 to identify, determine, infer, detect,
compute, predict, and/or anticipate, characteristics of user
activity on the device 250. Various inputs collected by the context
API 206 can be aggregated by the user activity module 215 to
generate a profile for characteristics of user activity. Such a
profile can be generated by the user activity module 215 with
various temporal characteristics. For instance, user activity
profile can be generated in real-time for a given instant to
provide a view of what the user is doing or not doing at a given
time (e.g., defined by a time window, in the last minute, in the
last 30 seconds, etc.), a user activity profile can also be
generated for a `session` defined by an application or web page
that describes the characteristics of user behavior with respect to
a specific task they are engaged in on the device 250, or for a
specific time period (e.g., for the last 2 hours, for the last 5
hours).
[0127] Additionally, characteristic profiles can be generated by
the user activity module 215 to depict a historical trend for user
activity and behavior (e.g., 1 week, 1 mo., 2 mo., etc.). Such
historical profiles can also be used to deduce trends of user
behavior, for example, access frequency at different times of day,
trends for certain days of the week (weekends or week days), user
activity trends based on location data (e.g., IP address, GPS, or
cell tower coordinate data) or changes in location data (e.g., user
activity based on user location, or user activity based on whether
the user is on the go, or traveling outside a home region, etc.) to
obtain user activity characteristics.
[0128] In one embodiment, user activity module 215 can detect and
track user activity with respect to applications, documents, files,
windows, icons, and folders on the device 250. For example, the
user activity module 215 can detect when an application or window
(e.g., a web browser or any other type of application) has been
exited, closed, minimized, maximized, opened, moved into the
foreground, or into the background, multimedia content playback,
etc.
[0129] In one embodiment, characteristics of the user activity on
the device 250 can be used to locally adjust behavior of the device
(e.g., mobile device or any wireless device) to optimize its
resource consumption such as battery/power consumption and more
generally, consumption of other device resources including memory,
storage, and processing power. In one embodiment, the use of a
radio on a device can be adjusted based on characteristics of user
behavior (e.g., by the radio controller 266 of the connection
manager 265) coupled to the user activity module 215. For example,
the radio controller 266 can turn the radio on or off, based on
characteristics of the user activity on the device 250. In
addition, the radio controller 266 can adjust the power mode of the
radio (e.g., to be in a higher power mode or lower power mode)
depending on characteristics of user activity.
[0130] In one embodiment, characteristics of the user activity on
device 250 can also be used to cause another device (e.g., other
computers, a mobile device, a wireless device, or a non-portable
device) or server (e.g., host server 100 and 300 in the examples of
FIG. 1A-B and FIG. 3A) which can communicate (e.g., via a cellular
or other network) with the device 250 to modify its communication
frequency with the device 250. The local proxy 275 can use the
characteristics information of user behavior determined by the user
activity module 215 to instruct the remote device as to how to
modulate its communication frequency (e.g., decreasing
communication frequency, such as data push frequency if the user is
idle, requesting that the remote device notify the device 250 if
new data, changed, data, or data of a certain level of importance
becomes available, etc.).
[0131] In one embodiment, the user activity module 215 can, in
response to determining that user activity characteristics indicate
that a user is active after a period of inactivity, request that a
remote device (e.g., server host server 100 and 300 in the examples
of FIG. 1A-B and FIG. 3A) send the data that was buffered as a
result of the previously decreased communication frequency.
[0132] In addition, or in alternative, the local proxy 275 can
communicate the characteristics of user activity at the device 250
to the remote device (e.g., host server 100 and 300 in the examples
of FIG. 1A-B and FIG. 3A) and the remote device determines how to
alter its own communication frequency with the device 250 for
network resource conservation and conservation of device 250
resources.
[0133] One embodiment of the local proxy 275 further includes a
request/transaction manager 235, which can detect, identify,
intercept, process, manage, data requests initiated on the device
250, for example, by applications 210 and/or 220, and/or
directly/indirectly by a user request. The request/transaction
manager 235 can determine how and when to process a given request
or transaction, or a set of requests/transactions, based on
transaction characteristics.
[0134] The request/transaction manager 235 can prioritize requests
or transactions made by applications and/or users at the device
250, for example by the prioritization engine 241. Importance or
priority of requests/transactions can be determined by the
request/transaction manager 235 by applying a rule set, for
example, according to time sensitivity of the transaction, time
sensitivity of the content in the transaction, time criticality of
the transaction, time criticality of the data transmitted in the
transaction, and/or time criticality or importance of an
application making the request.
[0135] In addition, transaction characteristics can also depend on
whether the transaction was a result of user-interaction or other
user-initiated action on the device (e.g., user interaction with a
application (e.g., a mobile application)). In general, a time
critical transaction can include a transaction resulting from a
user-initiated data transfer, and can be prioritized as such.
Transaction characteristics can also depend on the amount of data
that will be transferred or is anticipated to be transferred as a
result of the requested transaction. For example, the connection
manager 265, can adjust the radio mode (e.g., high power or low
power mode via the radio controller 266) based on the amount of
data that will need to be transferred.
[0136] In addition, the radio controller 266/connection manager 265
can adjust the radio power mode (high or low) based on time
criticality/sensitivity of the transaction. The radio controller
266 can trigger the use of high power radio mode when a
time-critical transaction (e.g., a transaction resulting from a
user-initiated data transfer, an application running in the
foreground, any other event meeting a certain criteria) is
initiated or detected.
[0137] In general, the priorities can be set by default, for
example, based on device platform, device manufacturer, operating
system, etc. Priorities can alternatively or in additionally be set
by the particular application; for example, the Facebook
application (e.g., a mobile application) can set its own priorities
for various transactions (e.g., a status update can be of higher
priority than an add friend request or a poke request, a message
send request can be of higher priority than a message delete
request, for example), an email client or IM chat client may have
its own configurations for priority. The prioritization engine 241
may include set of rules for assigning priority.
[0138] The prioritization engine 241 can also track network
provider limitations or specifications on application or
transaction priority in determining an overall priority status for
a request/transaction. Furthermore, priority can in part or in
whole be determined by user preferences, either explicit or
implicit. A user, can in general, set priorities at different
tiers, such as, specific priorities for sessions, or types, or
applications (e.g., a browsing session, a gaming session, versus an
IM chat session, the user may set a gaming session to always have
higher priority than an IM chat session, which may have higher
priority than web-browsing session). A user can set
application-specific priorities, (e.g., a user may set
Facebook-related transactions to have a higher priority than
LinkedIn-related transactions), for specific transaction types
(e.g., for all send message requests across all applications to
have higher priority than message delete requests, for all
calendar-related events to have a high priority, etc.), and/or for
specific folders.
[0139] The prioritization engine 241 can track and resolve
conflicts in priorities set by different entities. For example,
manual settings specified by the user may take precedence over
device OS settings, network provider parameters/limitations (e.g.,
set in default for a network service area, geographic locale, set
for a specific time of day, or set based on service/fee type) may
limit any user-specified settings and/or application-set
priorities. In some instances, a manual synchronization request
received from a user can override some, most, or all priority
settings in that the requested synchronization is performed when
requested, regardless of the individually assigned priority or an
overall priority ranking for the requested action.
[0140] Priority can be specified and tracked internally in any
known and/or convenient manner, including but not limited to, a
binary representation, a multi-valued representation, a graded
representation and all are considered to be within the scope of the
disclosed technology.
TABLE-US-00002 TABLE 2 Change Change (initiated on device) Priority
(initiated on server) Priority Send email High Receive email High
Delete email Low Edit email Often not possible to sync (Low if
possible) (Un)read email Low Move message Low New email in deleted
items Low Read more High Download attachment High Delete an email
Low (Un)Read an email Low New Calendar event High Move messages Low
Edit/change Calendar event High Any calendar change High Any
contact change High Add a contact High Wipe/lock device High Edit a
contact High Settings change High Search contacts High Any folder
change High Change a setting High Connector restart High (if no
changes nothing is sent) Manual send/receive High IM status change
Medium Social Network Status Updates Medium Auction outbid or
change High Sever Weather Alerts High notification Weather Updates
Low News Updates Low
[0141] Table 2 above shows, for illustration purposes, some
examples of transactions with examples of assigned priorities in a
binary representation scheme. Additional assignments are possible
for additional types of events, requests, transactions, and as
previously described, priority assignments can be made at more or
less granular levels, e.g., at the session level or at the
application level, etc.
[0142] As shown by way of example in the above table 2, in general,
lower priority requests/transactions can include, updating message
status as being read, unread, deleting of messages, deletion of
contacts; higher priority requests/transactions, can in some
instances include, status updates, new IM chat message, new email,
calendar event update/cancellation/deletion, an event in a mobile
gaming session, or other entertainment related events, a purchase
confirmation through a web purchase or online, request to load
additional or download content, contact book related events, a
transaction to change a device setting, location-aware or
location-based events/transactions, or any other
events/request/transactions initiated by a user or where the user
is known to be, expected to be, or suspected to be waiting for a
response, etc.
[0143] Inbox pruning events (e.g., email, or any other types of
messages), are generally considered low priority and absent other
impending events, generally will not trigger use of the radio on
the device 250. Specifically, pruning events to remove old email or
other content can be `piggy backed` with other communications if
the radio is not otherwise on, at the time of a scheduled pruning
event. For example, if the user has preferences set to `keep
messages for 7 days old,` then instead of powering on the device
radio to initiate a message delete from the device 250 the moment
that the message has exceeded 7 days old, the message is deleted
when the radio is powered on next. If the radio is already on, then
pruning may occur as regularly scheduled.
[0144] The request/transaction manager 235, can use the priorities
for requests (e.g., by the prioritization engine 241) to manage
outgoing traffic from the device 250 for resource optimization
(e.g., to utilize the device radio more efficiently for battery
conservation). For example, transactions/requests below a certain
priority ranking may not trigger use of the radio on the device 250
if the radio is not already switched on, as controlled by the
connection manager 265. In contrast, the radio controller 266 can
turn on the radio such a request can be sent when a request for a
transaction is detected to be over a certain priority level.
[0145] In one embodiment, priority assignments (such as that
determined by the local proxy 275 or another device/entity) can be
used cause a remote device to modify its communication with the
frequency with the mobile device or wireless device. For example,
the remote device can be configured to send notifications to the
device 250 when data of higher importance is available to be sent
to the mobile device or wireless device.
[0146] In one embodiment, transaction priority can be used in
conjunction with characteristics of user activity in shaping or
managing traffic, for example, by the traffic shaping engine 255.
For example, the traffic shaping engine 255 can, in response to
detecting that a user is dormant or inactive, wait to send low
priority transactions from the device 250, for a period of time. In
addition, the traffic shaping engine 255 can allow multiple low
priority transactions to accumulate for batch transferring from the
device 250 (e.g., via the batching module 257). In one embodiment,
the priorities can be set, configured, or readjusted by a user. For
example, content depicted in Table 2 in the same or similar form
can be accessible in a user interface on the device 250 and for
example, used by the user to adjust or view the priorities.
[0147] The batching module 257 can initiate batch transfer based on
certain criteria. For example, batch transfer (e.g., of multiple
occurrences of events, some of which occurred at different
instances in time) may occur after a certain number of low priority
events have been detected, or after an amount of time elapsed after
the first of the low priority event was initiated. In addition, the
batching module 257 can initiate batch transfer of the cumulated
low priority events when a higher priority event is initiated or
detected at the device 250. Batch transfer can otherwise be
initiated when radio use is triggered for another reason (e.g., to
receive data from a remote device such as host server 100 or 300).
In one embodiment, an impending pruning event (pruning of an
inbox), or any other low priority events, can be executed when a
batch transfer occurs.
[0148] In general, the batching capability can be disabled or
enabled at the event/transaction level, application level, or
session level, based on any one or combination of the following:
user configuration, device limitations/settings, manufacturer
specification, network provider parameters/limitations,
platform-specific limitations/settings, device OS settings, etc. In
one embodiment, batch transfer can be initiated when an
application/window/file is closed out, exited, or moved into the
background; users can optionally be prompted before initiating a
batch transfer; users can also manually trigger batch
transfers.
[0149] In one embodiment, the local proxy 275 locally adjusts radio
use on the device 250 by caching data in the cache 285. When
requests or transactions from the device 250 can be satisfied by
content stored in the cache 285, the radio controller 266 need not
activate the radio to send the request to a remote entity (e.g.,
the host server 100, 300, as shown in FIG. 1A and FIG. 3A or a
content provider/application server such as the server/provider 110
shown in the examples of FIG. 1A and FIG. 1B). As such, the local
proxy 275 can use the local cache 285 and the cache policy manager
245 to locally store data for satisfying data requests to eliminate
or reduce the use of the device radio for conservation of network
resources and device battery consumption.
[0150] In leveraging the local cache, once the request/transaction
manager 225 intercepts a data request by an application on the
device 250, the local repository 285 can be queried to determine if
there is any locally stored response, and also determine whether
the response is valid. When a valid response is available in the
local cache 285, the response can be provided to the application on
the device 250 without the device 250 needing to access the
cellular network or wireless broadband network.
[0151] If a valid response is not available, the local proxy 275
can query a remote proxy (e.g., the server proxy 325 of FIG. 3A) to
determine whether a remotely stored response is valid. If so, the
remotely stored response (e.g., which may be stored on the server
cache 135 or optional caching server 199 shown in the example of
FIG. 1B) can be provided to the mobile device, possibly without the
mobile device 250 needing to access the cellular network, thus
relieving consumption of network resources.
[0152] If a valid cache response is not available, or if cache
responses are unavailable for the intercepted data request, the
local proxy 275, for example, the caching policy manager 245, can
send the data request to a remote proxy (e.g., server proxy 325 of
FIG. 3A) which forwards the data request to a content source (e.g.,
application server/content provider 110 of FIG. 1A) and a response
from the content source can be provided through the remote proxy,
as will be further described in the description associated with the
example host server 300 of FIG. 3A. The cache policy manager 245
can manage or process requests that use a variety of protocols,
including but not limited to HTTP, HTTPS, IMAP, POP, SMTP, XMPP,
and/or ActiveSync. The caching policy manager 245 can locally store
responses for data requests in the local database 285 as cache
entries, for subsequent use in satisfying same or similar data
requests.
[0153] The caching policy manager 245 can request that the remote
proxy monitor responses for the data request and the remote proxy
can notify the device 250 when an unexpected response to the data
request is detected. In such an event, the cache policy manager 245
can erase or replace the locally stored response(s) on the device
250 when notified of the unexpected response (e.g., new data,
changed data, additional data, etc.) to the data request. In one
embodiment, the caching policy manager 245 is able to detect or
identify the protocol used for a specific request, including but
not limited to HTTP, HTTPS, IMAP, POP, SMTP, XMPP, and/or
ActiveSync. In one embodiment, application specific handlers (e.g.,
via the application protocol module 246 of the caching policy
manager 245) on the local proxy 275 allows for optimization of any
protocol that can be port mapped to a handler in the distributed
proxy (e.g., port mapped on the proxy server 325 in the example of
FIG. 3A).
[0154] In one embodiment, the local proxy 275 notifies the remote
proxy such that the remote proxy can monitor responses received for
the data request from the content source for changed results prior
to returning the result to the device 250, for example, when the
data request to the content source has yielded same results to be
returned to the mobile device. In general, the local proxy 275 can
simulate application server responses for applications on the
device 250, using locally cached content. This can prevent
utilization of the cellular network for transactions where
new/changed data is not available, thus freeing up network
resources and preventing network congestion.
[0155] In one embodiment, the local proxy 275 includes an
application behavior detector 236 to track, detect, observe,
monitor, applications (e.g., proxy-aware and/or unaware
applications 210 and 220) accessed or installed on the device 250.
Application behaviors, or patterns in detected behaviors (e.g., via
the pattern detector 237) of one or more applications accessed on
the device 250 can be used by the local proxy 275 to optimize
traffic in a wireless network needed to satisfy the data needs of
these applications.
[0156] For example, based on detected behavior of multiple
applications, the traffic shaping engine 255 can align content
requests made by at least some of the applications over the network
(wireless network) (e.g., via the alignment module 256). The
alignment module 256 can delay or expedite some earlier received
requests to achieve alignment. When requests are aligned, the
traffic shaping engine 255 can utilize the connection manager to
poll over the network to satisfy application data requests. Content
requests for multiple applications can be aligned based on behavior
patterns or rules/settings including, for example, content types
requested by the multiple applications (audio, video, text, etc.),
device (e.g., mobile or wireless device) parameters, and/or network
parameters/traffic conditions, network service provider
constraints/specifications, etc.
[0157] In one embodiment, the pattern detector 237 can detect
recurrences in application requests made by the multiple
applications, for example, by tracking patterns in application
behavior. A tracked pattern can include, detecting that certain
applications, as a background process, poll an application server
regularly, at certain times of day, on certain days of the week,
periodically in a predictable fashion, with a certain frequency,
with a certain frequency in response to a certain type of event, in
response to a certain type user query, frequency that requested
content is the same, frequency with which a same request is made,
interval between requests, applications making a request, or any
combination of the above, for example.
[0158] Such recurrences can be used by traffic shaping engine 255
to offload polling of content from a content source (e.g., from an
application server/content provider 110 of FIG. 1A) that would
result from the application requests that would be performed at the
mobile device or wireless device 250 to be performed instead, by a
proxy server (e.g., proxy server 125 of FIG. 1B or proxy server 325
of FIG. 3A) remote from the device 250. Traffic shaping engine 255
can decide to offload the polling when the recurrences match a
rule. For example, there are multiple occurrences or requests for
the same resource that have exactly the same content, or returned
value, or based on detection of repeatable time periods between
requests and responses such as a resource that is requested at
specific times during the day. The offloading of the polling can
decrease the amount of bandwidth consumption needed by the mobile
device 250 to establish a wireless (cellular or other wireless
broadband) connection with the content source for repetitive
content polls.
[0159] As a result of the offloading of the polling, locally cached
content stored in the local cache 285 can be provided to satisfy
data requests at the device 250, when content change is not
detected in the polling of the content sources. As such, when data
has not changed, application data needs can be satisfied without
needing to enable radio use or occupying cellular bandwidth in a
wireless network. When data has changed and/or new data has been
received, the remote entity to which polling is offloaded, can
notify the device 250. The remote entity may be the host server 300
as shown in the example of FIG. 3A.
[0160] In one embodiment, the local proxy 275 can mitigate the
need/use of periodic keep-alive messages (heartbeat messages) to
maintain TCP/IP connections, which can consume significant amounts
of power thus having detrimental impacts on mobile device battery
life. The connection manager 265 in the local proxy (e.g., the
heartbeat manager 267) can detect, identify, and intercept any or
all heartbeat (keep-alive) messages being sent from
applications.
[0161] The heartbeat manager 267 can prevent any or all of these
heartbeat messages from being sent over the cellular, or other
network, and instead rely on the server component of the
distributed proxy system (e.g., shown in FIG. 1B) to generate the
and send the heartbeat messages to maintain a connection with the
backend (e.g., application server/provider 110 in the example of
FIG. 1A).
[0162] The local proxy 275 generally represents any one or a
portion of the functions described for the individual managers,
modules, and/or engines. The local proxy 275 and device 250 can
include additional or less components; more or less functions can
be included, in whole or in part, without deviating from the novel
art of the disclosure.
[0163] FIG. 2B depicts a block diagram illustrating a further
example of components in the cache system shown in the example of
FIG. 2A which is capable of caching and adapting caching strategies
for mobile application behavior and/or network conditions.
[0164] In one embodiment, the caching policy manager 245 includes a
metadata generator 203, a cache look-up engine 205, a cache
appropriateness decision engine 246, a poll schedule generator 247,
an application protocol module 248, a cache or connect selection
engine 249 and/or a local cache invalidator 244. The cache
appropriateness decision engine 246 can further include a timing
predictor 246a,a content predictor 246b, a request analyzer 246c,
and/or a response analyzer 246d, and the cache or connect selection
engine 249 includes a response scheduler 249a. The metadata
generator 203 and/or the cache look-up engine 205 are coupled to
the cache 285 (or local cache) for modification or addition to
cache entries or querying thereof.
[0165] The cache look-up engine 205 may further include an ID or
URI filter 205a, the local cache invalidator 244 may further
include a TTL manager 244a, and the poll schedule generator 247 may
further include a schedule update engine 247a and/or a time
adjustment engine 247b. One embodiment of caching policy manager
245 includes an application cache policy repository 243. In one
embodiment, the application behavior detector 236 includes a
pattern detector 237, a poll interval detector 238, an application
profile generator 239, and/or a priority engine 241. The poll
interval detector 238 may further include a long poll detector 238a
having a response/request tracking engine 238b. The poll interval
detector 238 may further include a long poll hunting detector 238c.
The application profile generator 239 can further include a
response delay interval tracker 239a.
[0166] The pattern detector 237, application profile generator 239,
and the priority engine 241 were also described in association with
the description of the pattern detector shown in the example of
FIG. 2A. One embodiment further includes an application profile
repository 242 which can be used by the local proxy 275 to store
information or metadata regarding application profiles (e.g.,
behavior, patterns, type of HTTP requests, etc.)
[0167] The cache appropriateness decision engine 246 can detect,
assess, or determine whether content from a content source (e.g.,
application server/content provider 110 in the example of FIG. 1B)
with which a mobile device 250 interacts and has content that may
be suitable for caching. For example, the decision engine 246 can
use information about a request and/or a response received for the
request initiated at the mobile device 250 to determine
cacheability, potential cacheability, or non-cacheability. In some
instances, the decision engine 246 can initially verify whether a
request is directed to a blacklisted destination or whether the
request itself originates from a blacklisted client or application.
If so, additional processing and analysis may not be performed by
the decision engine 246 and the request may be allowed to be sent
over the air to the server to satisfy the request. The black listed
destinations or applications/clients (e.g., mobile applications)
can be maintained locally in the local proxy (e.g., in the
application profile repository 242) or remotely (e.g., in the proxy
server 325 or another entity).
[0168] In one embodiment, the decision engine 246, for example, via
the request analyzer 246c, collects information about an
application or client request generated at the mobile device 250.
The request information can include request characteristics
information including, for example, request method. For example,
the request method can indicate the type of HTTP request generated
by the mobile application or client. In one embodiment, response to
a request can be identified as cacheable or potentially cacheable
if the request method is a GET request or POST request. Other types
of requests (e.g., OPTIONS, HEAD, PUT, DELETE, TRACE, or CONNECT)
may or may not be cached. In general, HTTP requests with
uncacheable request methods will not be cached.
[0169] Request characteristics information can further include
information regarding request size, for example. Responses to
requests (e.g., HTTP requests) with body size exceeding a certain
size will not be cached. For example, cacheability can be
determined if the information about the request indicates that a
request body size of the request does not exceed a certain size. In
some instances, the maximum cacheable request body size can be set
to 8092 bytes. In other instances, different values may be used,
dependent on network capacity or network operator specific
settings, for example.
[0170] In some instances, content from a given application
server/content provider (e.g., the server/content provider 110 of
FIG. 1B) is determined to be suitable for caching based on a set of
criteria, for example, criteria specifying time criticality of the
content that is being requested from the content source. In one
embodiment, the local proxy (e.g., the local proxy 175 or 275 of
FIG. 1B and FIG. 2A) applies a selection criteria to store the
content from the host server which is requested by an application
as cached elements in a local cache on the mobile device to satisfy
subsequent requests made by the application.
[0171] The cache appropriateness decision engine 246, further based
on detected patterns of requests sent from the mobile device 250
(e.g., by a mobile application or other types of clients on the
device 250) and/or patterns of received responses, can detect
predictability in requests and/or responses. For example, the
request characteristics information collected by the decision
engine 246, (e.g., the request analyzer 246c) can further include
periodicity information between a request and other requests
generated by a same client on the mobile device or other requests
directed to the same host (e.g., with similar or same identifier
parameters).
[0172] Periodicity can be detected, by the decision engine 246 or
the request analyzer 246c, when the request and the other requests
generated by the same client occur at a fixed rate or nearly fixed
rate, or at a dynamic rate with some identifiable or partially or
wholly reproducible changing pattern. If the requests are made with
some identifiable pattern (e.g., regular intervals, intervals
having a detectable pattern, or trend (e.g., increasing,
decreasing, constant, etc.) the timing predictor 246a can determine
that the requests made by a given application on a device is
predictable and identify it to be potentially appropriate for
caching, at least from a timing standpoint.
[0173] An identifiable pattern or trend can generally include any
application or client behavior which may be simulated either
locally, for example, on the local proxy 275 on the mobile device
250 or simulated remotely, for example, by the proxy server 325 on
the host 300, or a combination of local and remote simulation to
emulate application behavior.
[0174] In one embodiment, the decision engine 246, for example, via
the response analyzer 246d, can collect information about a
response to an application or client request generated at the
mobile device 250. The response is typically received from a server
or the host of the application (e.g., mobile application) or client
which sent the request at the mobile device 250. In some instances,
the mobile client or application can be the mobile version of an
application (e.g., social networking, search, travel management,
voicemail, contact manager, email) or a web site accessed via a web
browser or via a desktop client.
[0175] For example, response characteristics information can
include an indication of whether transfer encoding or chunked
transfer encoding is used in sending the response. In some
instances, responses to HTTP requests with transfer encoding or
chunked transfer encoding are not cached, and therefore are also
removed from further analysis. The rationale here is that chunked
responses are usually large and non-optimal for caching, since the
processing of these transactions may likely slow down the overall
performance Therefore, in one embodiment, cacheability or potential
for cacheability can be determined when transfer encoding is not
used in sending the response.
[0176] In addition, the response characteristics information can
include an associated status code of the response which can be
identified by the response analyzer 246d. In some instances, HTTP
responses with uncacheable status codes are typically not cached.
The response analyzer 246d can extract the status code from the
response and determine whether it matches a status code which is
cacheable or uncacheable. Some cacheable status codes include by
way of example: 200--OK, 301--Redirect, 302--Found, 303--See other,
304--Not Modified, 307Temporary Redirect, or 500--Internal server
error. Some uncacheable status codes can include, for example,
403--Forbidden or 404--Not found.
[0177] In one embodiment, cacheability or potential for
cacheability can be determined if the information about the
response does not indicate an uncacheable status code or indicates
a cacheable status code. If the response analyzer 246d detects an
uncacheable status code associated with a given response, the
specific transaction (request/response pair) may be eliminated from
further processing and determined to be uncacheable on a temporary
basis, a semi-permanent, or a permanent basis. If the status code
indicates cacheability, the transaction (e.g., request and/or
response pair) may be subject to further processing and analysis to
confirm cacheability.
[0178] Response characteristics information can also include
response size information. In general, responses can be cached
locally at the mobile device 250 if the responses do not exceed a
certain size. In some instances, the default maximum cached
response size is set to 128 KB. In other instances, the max
cacheable response size may be different and/or dynamically
adjusted based on operating conditions, network conditions, network
capacity, user preferences, network operator requirements, or other
application-specific, user specific, and/or device-specific
reasons. In one embodiment, the response analyzer 246d can identify
the size of the response, and cacheability or potential for
cacheability can be determined if a given threshold or max value is
not exceeded by the response size.
[0179] Furthermore, response characteristics information can
include response body information for the response to the request
and other response to other requests generated by a same client on
the mobile device, or directed to a same content host or
application server. The response body information for the response
and the other responses can be compared, for example, by the
response analyzer 246d, to prevent the caching of dynamic content
(or responses with content that changes frequently and cannot be
efficiently served with cache entries, such as financial data,
stock quotes, news feeds, real-time sporting event activities,
etc.), such as content that would no longer be relevant or
up-to-date if served from cached entries.
[0180] The cache appropriateness decision engine 246 (e.g., the
content predictor 246b) can definitively identify repeatability or
identify indications of repeatability, potential repeatability, or
predictability in responses received from a content source (e.g.,
the content host/application server 110 shown in the example of
FIG. 1A-B). Repeatability can be detected by, for example, tracking
at least two responses received from the content source and
determines if the two responses are the same. For example,
cacheability can be determined, by the response analyzer 246d, if
the response body information for the response and the other
responses sent by the same mobile client or directed to the same
host/server are same or substantially the same. The two responses
may or may not be responses sent in response to consecutive
requests. In one embodiment, hash values of the responses received
for requests from a given application are used to determine
repeatability of content (with or without heuristics) for the
application in general and/or for the specific request. Additional
same responses may be required for some applications or under
certain circumstances.
[0181] Repeatability in received content need not be 100%
ascertained. For example, responses can be determined to be
repeatable if a certain number or a certain percentage of responses
are the same, or similar. The certain number or certain percentage
of same/similar responses can be tracked over a select period of
time, set by default or set based on the application generating the
requests (e.g., whether the application is highly dynamic with
constant updates or less dynamic with infrequent updates). Any
indicated predictability or repeatability, or possible
repeatability, can be utilized by the distributed system in caching
content to be provided to a requesting application or client on the
mobile device 250.
[0182] In one embodiment, for a long poll type request, the local
proxy 175 can begin to cache responses on a third request when the
response delay times for the first two responses are the same,
substantially the same, or detected to be increasing in intervals.
In general, the received responses for the first two responses
should be the same, and upon verifying that the third response
received for the third request is the same (e.g., if R0=R1=R2), the
third response can be locally cached on the mobile device. Less or
more same responses may be required to begin caching, depending on
the type of application, type of data, type of content, user
preferences, or carrier/network operator specifications.
[0183] Increasing response delays with same responses for long
polls can indicate a hunting period (e.g., a period in which the
application/client on the mobile device is seeking the longest time
between a request and response that a given network will allow, a
timing diagram showing timing characteristics is illustrated in
FIG. 8), as detected by the long poll hunting detector 238c of the
application behavior detector 236.
[0184] An example can be described below using T0, T1, T2, where T
indicates the delay time between when a request is sent and when a
response (e.g., the response header) is detected/received for
consecutive requests: [0185] T0=Response0(t)-Request0(t)=180 s.
(+/-tolerance) [0186] T1=Response1(t)-Request1 (t)=240 s.
(+/-tolerance) [0187] T2=Response2(t)-Request2(t)=500 s.
(+/-tolerance)
[0188] In the example timing sequence shown above, T0<T1<T2,
this may indicate a hunting pattern for a long poll when network
timeout has not yet been reached or exceeded. Furthermore, if the
responses R0, R1, and R2 received for the three requests are the
same, R2 can be cached. In this example, R2 is cached during the
long poll hunting period without waiting for the long poll to
settle, thus expediting response caching (e.g., this is optional
accelerated caching behavior which can be implemented for all or
select applications).
[0189] As such, the local proxy 275 can specify information that
can be extracted from the timing sequence shown above (e.g.,
polling schedule, polling interval, polling type) to the proxy
server and begin caching and to request the proxy server to begin
polling and monitoring the source (e.g., using any of T0, T1, T2 as
polling intervals but typically T2, or the largest detected
interval without timing out, and for which responses from the
source is received will be sent to the proxy server 325 of FIG. 3A
for use in polling the content source (e.g., application
server/service provider 310)).
[0190] However, if the time intervals are detected to be getting
shorter, the application (e.g., mobile application)/client may
still be hunting for a time interval for which a response can be
reliably received from the content source (e.g., application/server
server/provider 110 or 310), and as such caching typically should
not begin until the request/response intervals indicate the same
time interval or an increasing time interval, for example, for a
long poll type request.
[0191] An example of handling a detected decreasing delay can be
described below using T0, T1, T2, T3, and T4 where T indicates the
delay time between when a request is sent and when a response
(e.g., the response header) is detected/received for consecutive
requests: [0192] T0=Response0(t)-Request0(t)=160 s. (+/-tolerance)
[0193] T1=Response1(t)-Request1 (t)=240 s. (+/-tolerance) [0194]
T2=Response2(t)-Request2(t)=500 s. (+/-tolerance) [0195] T3=Time
out at 700 s. (+/-tolerance) [0196] T4=Response4(t)-Request4(t)=600
(+/-tolerance)
[0197] If a pattern for response delays T1<T2<T3>T4 is
detected, as shown in the above timing sequence (e.g., detected by
the long poll hunting detector 238c of the application behavior
detector 236), it can be determined that T3 likely exceeded the
network time out during a long poll hunting period. In Request 3, a
response likely was not received since the connection was
terminated by the network, application, server, or other reason
before a response was sent or available. On Request 4 (after T4),
if a response (e.g., Response 4) is detected or received, the local
proxy 275 can then use the response for caching (if the content
repeatability condition is met). The local proxy can also use T4 as
the poll interval in the polling schedule set for the proxy server
to monitor/poll the content source.
[0198] Note that the above description shows that caching can begin
while long polls are in hunting mode in the event of detecting
increasing response delays, as long as responses are received and
not timed out for a given request. This can be referred to as the
optional accelerated caching during long poll hunting. Caching can
also begin after the hunting mode (e.g., after the poll requests
have settled to a constant or near constant delay value) has
completed. Note that hunting may or may not occur for long polls
and when hunting occurs; the proxy 275 can generally detect this
and determine whether to begin to cache during the hunting period
(increasing intervals with same responses) or wait until the hunt
settles to a stable value.
[0199] In one embodiment, the timing predictor 246a of the cache
appropriateness decision engine 246 can track timing of responses
received from outgoing requests from an application (e.g., mobile
application) or client to detect any identifiable patterns which
can be partially wholly reproducible, such that locally cached
responses can be provided to the requesting client on the mobile
device 250 in a manner that simulates content source (e.g.,
application server/content provider 110 or 310) behavior. For
example, the manner in which (e.g., from a timing standpoint)
responses or content would be delivered to the requesting
application/client on the device 250. This ensures preservation of
user experience when responses to application or mobile client
requests are served from a local and/or remote cache instead of
being retrieved/received directly from the content source (e.g.,
application, content provider 110 or 310).
[0200] In one embodiment, the decision engine 246 or the timing
predictor 246a determines the timing characteristics a given
application (e.g., mobile application) or client from, for example,
the request/response tracking engine 238b and/or the application
profile generator 239 (e.g., the response delay interval tracker
239a). Using the timing characteristics, the timing predictor 246a
determines whether the content received in response to the requests
are suitable or are potentially suitable for caching. For example,
poll request intervals between two consecutive requests from a
given application can be used to determine whether request
intervals are repeatable (e.g., constant, near constant, increasing
with a pattern, decreasing with a pattern, etc.) and can be
predicted and thus reproduced at least some of the times either
exactly or approximated within a tolerance level.
[0201] In some instances, the timing characteristics of a given
request type for a specific application, for multiple requests of
an application, or for multiple applications can be stored in the
application profile repository 242. The application profile
repository 242 can generally store any type of information or
metadata regarding application request/response characteristics
including timing patterns, timing repeatability, content
repeatability, etc.
[0202] The application profile repository 242 can also store
metadata indicating the type of request used by a given application
(e.g., long polls, long-held HTTP requests, HTTP streaming, push,
COMET push, etc.) Application profiles indicating request type by
applications can be used when subsequent same/similar requests are
detected, or when requests are detected from an application which
has already been categorized. In this manner, timing
characteristics for the given request type or for requests of a
specific application which has been tracked and/or analyzed, need
not be reanalyzed.
[0203] Application profiles can be associated with a time-to-live
(e.g., or a default expiration time). The use of an expiration time
for application profiles, or for various aspects of an application
or request's profile can be used on a case by case basis. The
time-to-live or actual expiration time of application profile
entries can be set to a default value or determined individually,
or a combination thereof. Application profiles can also be specific
to wireless networks, physical networks, network operators, or
specific carriers.
[0204] One embodiment includes an application blacklist manager
201. The application blacklist manager 201 can be coupled to the
application cache policy repository 243 and can be partially or
wholly internal to local proxy or the caching policy manager 245.
Similarly, the blacklist manager 201 can be partially or wholly
internal to local proxy or the application behavior detector 236.
The blacklist manager 201 can aggregate, track, update, manage,
adjust, or dynamically monitor a list of destinations of
servers/host that are `blacklisted,` or identified as not cached,
on a permanent or temporary basis. The blacklist of destinations,
when identified in a request, can potentially be used to allow the
request to be sent over the (cellular) network for servicing.
Additional processing on the request may not be performed since it
is detected to be directed to a blacklisted destination.
[0205] Blacklisted destinations can be identified in the
application cache policy repository 243 by address identifiers
including specific URIs or patterns of identifiers including URI
patterns. In general, blacklisted destinations can be set by or
modified for any reason by any party including the user (owner/user
of mobile device 250), operating system/mobile platform of device
250, the destination itself, network operator (of cellular
network), Internet service provider, other third parties, or
according to a list of destinations for applications known to be
uncacheable/not suited for caching. Some entries in the blacklisted
destinations may include destinations aggregated based on the
analysis or processing performed by the local proxy (e.g., cache
appropriateness decision engine 246).
[0206] For example, applications or mobile clients on the mobile
device for which responses have been identified as non-suitable for
caching can be added to the blacklist. Their corresponding
hosts/servers may be added in addition to or in lieu of an
identification of the requesting application/client on the mobile
device 250. Some or all of such clients identified by the proxy
system can be added to the blacklist. For example, for all
application clients or applications that are temporarily identified
as not being suitable for caching, only those with certain detected
characteristics (based on timing, periodicity, frequency of
response content change, content predictability, size, etc.) can be
blacklisted.
[0207] The blacklisted entries may include a list of requesting
applications or requesting clients on the mobile device (rather
than destinations) such that, when a request is detected from a
given application or given client, it may be sent through the
network for a response, since responses for blacklisted
clients/applications are in most circumstances not cached.
[0208] A given application profile may also be treated or processed
differently (e.g., different behavior of the local proxy 275 and
the remote proxy 325) depending on the mobile account associated
with a mobile device from which the application is being accessed.
For example, a higher paying account, or a premier account may
allow more frequent access of the wireless network or higher
bandwidth allowance thus affecting the caching policies implemented
between the local proxy 275 and proxy server 325 with an emphasis
on better performance compared to conservation of resources. A
given application profile may also be treated or processed
differently under different wireless network conditions (e.g.,
based on congestion or network outage, etc.).
[0209] Note that cache appropriateness can be determined, tracked,
and managed for multiple clients or applications on the mobile
device 250. Cache appropriateness can also be determined for
different requests or request types initiated by a given client or
application on the mobile device 250. The caching policy manager
245, along with the timing predictor 246a and/or the content
predictor 246b which heuristically determines or estimates
predictability or potential predictability, can track, manage and
store cacheability information for various application or various
requests for a given application. Cacheability information may also
include conditions (e.g., an application can be cached at certain
times of the day, or certain days of the week, or certain requests
of a given application can be cached, or all requests with a given
destination address can be cached) under which caching is
appropriate which can be determined and/or tracked by the cache
appropriateness decision engine 246 and stored and/or updated when
appropriate in the application cache policy repository 243 coupled
to the cache appropriateness decision engine 246.
[0210] The information in the application cache policy repository
243 regarding cacheability of requests, applications, and/or
associated conditions can be used later on when same requests are
detected. In this manner, the decision engine 246 and/or the timing
and content predictors 246a/b need not track and reanalyze
request/response timing and content characteristics to make an
assessment regarding cacheability. In addition, the cacheability
information can in some instances be shared with local proxies of
other mobile devices by way of direct communication or via the host
server (e.g., proxy server 325 of host server 300).
[0211] For example, cacheability information detected by the local
proxy 275 on various mobile devices can be sent to a remote host
server or a proxy server 325 on the host server (e.g., host server
300 or proxy server 325 shown in the example of FIG. 3A, host 100
and proxy server 125 in the example of FIG. 1A-B). The remote host
or proxy server can then distribute the information regarding
application-specific, request-specific cacheability information
and/or any associated conditions to various mobile devices or their
local proxies in a wireless network or across multiple wireless
networks (same service provider or multiple wireless service
providers) for their use.
[0212] In general, the selection criteria for caching can further
include, by way of example but not limitation, the state of the
mobile device indicating whether the mobile device is active or
inactive, network conditions, and/or radio coverage statistics. The
cache appropriateness decision engine 246 can in any one or any
combination of the criteria, and in any order, identifying sources
for which caching may be suitable.
[0213] Once application servers/content providers having identified
or detected content that is potentially suitable for local caching
on the mobile device 250, the cache policy manager 245 can proceed
to cache the associated content received from the identified
sources by storing content received from the content source as
cache elements in a local cache (e.g., local cache 185 or 285 shown
in the examples of FIG. 1B and FIG. 2A, respectively) on the mobile
device 250.
[0214] The response can be stored in the cache 285 (e.g., also
referred as the local cache) as a cache entry. In addition to the
response to a request, the cached entry can include response
metadata having additional information regarding caching of the
response. The metadata may be generated by the metadata generator
203 and can include, for example, timing data such as the access
time of the cache entry or creation time of the cache entry.
Metadata can include additional information, such as any
information suited for use in determining whether the response
stored as the cached entry is used to satisfy the subsequent
response. For example, metadata information can further include,
request timing history (e.g., including request time, request start
time, request end time), hash of the request and/or response, time
intervals or changes in time intervals, etc.
[0215] The cache entry is typically stored in the cache 285 in
association with a time-to-live (TTL), which for example may be
assigned or determined by the TTL manager 244a of the cache
invalidator 244. The time-to-live of a cache entry is the amount of
time the entry is persisted in the cache 285 regardless of whether
the response is still valid or relevant for a given request or
client/application on the mobile device 250. For example, if the
time-to-live of a given cache entry is set to 12 hours, the cache
entry is purged, removed, or otherwise indicated as having exceeded
the time-to-live, even if the response body contained in the cache
entry is still current and applicable for the associated
request.
[0216] A default time-to-live can be automatically used for all
entries unless otherwise specified (e.g., by the TTL manager 244a),
or each cache entry can be created with its individual TTL (e.g.,
determined by the TTL manager 244a based on various dynamic or
static criteria). Note that each entry can have a single
time-to-live associated with both the response data and any
associated metadata. In some instances, the associated metadata may
have a different time-to-live (e.g., a longer time-to-live) than
the response data.
[0217] The content source having content for caching can, in
addition or in alternate, be identified to a proxy server (e.g.,
proxy server 125 or 325 shown in the examples of FIG. 1B and FIG.
3A, respectively) remote from and in wireless communication with
the mobile device 250 such that the proxy server can monitor the
content source (e.g., application server/content provider 110) for
new or changed data. Similarly, the local proxy (e.g., the local
proxy 175 or 275 of FIG. 1B and FIG. 2A, respectively) can identify
to the proxy server that content received from a specific
application server/content provider is being stored as cached
elements in the local cache 285.
[0218] Once content has been locally cached, the cache policy
manager 245, upon receiving future polling requests to contact the
application server/content host (e.g., 110 or 310), can retrieve
the cached elements from the local cache to respond to the polling
request made at the mobile device 250 such that a radio of the
mobile device is not activated to service the polling request. For
example, the cache look-up engine 205 can query the cache 285 to
identify the response to be served to a response. The response can
be served from the cache in response to identifying a matching
cache entry and also using any metadata stored with the response in
the cache entry. The cache entries can be queried by the cache
look-up engine using a URI of the request or another type of
identifier (e.g., via the ID or URI filter 205a). The cache-lookup
engine 205 can further use the metadata (e.g., extract any timing
information or other relevant information) stored with the matching
cache entry to determine whether response is still suited for use
in being served to a current request.
[0219] Note that the cache-look-up can be performed by the engine
205 using one or more of various multiple strategies. In one
embodiment, multiple cook-up strategies can be executed
sequentially on each entry store din the cache 285, until at least
one strategy identifies a matching cache entry. The strategy
employed to performing cache look-up can include a strict matching
criteria or a matching criteria which allows for non-matching
parameters.
[0220] For example, the look-up engine 205 can perform a strict
matching strategy which searches for an exact match between an
identifier (e.g., a URI for a host or resource) referenced in a
present request for which the proxy is attempting to identify a
cache entry and an identifier stored with the cache entries. In the
case where identifiers include URIs or URLs, the matching algorithm
for strict matching will search for a cache entry where all the
parameters in the URLs match. For example:
Example 1
[0221] 1. Cache contains entry for http://test.com/products/
[0222] 2. Request is being made to URI
http://test.com/products/
Strict strategy will find a match, since both URIs are same.
Example 2
[0223] 1. Cache contains entry for
http://test.com/products/?query=all
[0224] 2. Request is being made to URI
http://test.com/products/?query=sub
[0225] Under the strict strategy outlined above, a match will not
be found since the URIs differ in the query parameter.
[0226] In another example strategy, the look-up engine 205 looks
for a cache entry with an identifier that partially matches the
identifier references in a present request for which the proxy is
attempting to identify a matching cache entry. For example, the
look-up engine 205 may look for a cache entry with an identifier
which differs from the request identifier by a query parameter
value. In utilizing this strategy, the look-up engine 205 can
collect information collected for multiple previous requests (e.g.,
a list of arbitrary parameters in an identifier) to be later
checked with the detected arbitrary parameter in the current
request. For example, in the case where cache entries are stored
with URI or URL identifiers, the look-up engine searches for a
cache entry with a URI differing by a query parameter. If found,
the engine 205 can examine the cache entry for information
collected during previous requests (e.g. a list of arbitrary
parameters) and checked whether the arbitrary parameter detected in
or extracted from the current URI/URL belongs to the arbitrary
parameters list.
Example 1
[0227] 1. Cache contains entry for
http://test.com/products/?query=a11, where query is marked as
arbitrary.
[0228] 2. Request is being made to URI
http://text.com/products/?query=sub
Match will be found, since query parameter is marked as
arbitrary.
Example 2
[0229] 1. Cache contains entry for
http://test.com/products/?query=a11, where query is marked as
arbitrary.
[0230] 2. Request is being made to URI
http://test.com/products/?query=sub&sort=asc
Match will not be found, since current request contains sort
parameter which is not marked as arbitrary in the cache entry.
[0231] Additional strategies for detecting cache hit may be
employed. These strategies can be implemented singly or in any
combination thereof. A cache-hit can be determined when any one of
these strategies determines a match. A cache miss may be indicated
when the look-up engine 205 determines that the requested data
cannot be served from the cache 285, for any reason. For example, a
cache miss may be determined when no cache entries are identified
for any or all utilized look-up strategies.
[0232] Cache miss may also be determined when a matching cache
entry exists but determined to be invalid or irrelevant for the
current request. For example, the look-up engine 205 may further
analyze metadata (e.g., which may include timing data of the cache
entry) associated with the matching cache entry to determine
whether it is still suitable for use in responding to the present
request.
[0233] When the look-up engine 205 has identified a cache hit
(e.g., an event indicating that the requested data can be served
from the cache), the stored response in the matching cache entry
can be served from the cache to satisfy the request of an
application/client.
[0234] By servicing requests using cache entries stored in cache
285, network bandwidth and other resources need not be used to
request/receive poll responses which may have not changed from a
response that has already been received at the mobile device 250.
Such servicing and fulfilling application (e.g., mobile
application) requests locally via cache entries in the local cache
285 allows for more efficient resource and mobile network traffic
utilization and management since the request need not be sent over
the wireless network further consuming bandwidth. In general, the
cache 285 can be persisted between power on/off of the mobile
device 250, and persisted across application/client refreshes and
restarts.
[0235] For example, the local proxy 275, upon receipt of an
outgoing request from its mobile device 250 or from an application
or other type of client on the mobile device 250, can intercept the
request and determine whether a cached response is available in the
local cache 285 of the mobile device 250. If so, the outgoing
request is responded to by the local proxy 275 using the cached
response on the cache of the mobile device. As such, the outgoing
request can be filled or satisfied without a need to send the
outgoing request over the wireless network, thus conserving network
resources and battery consumption.
[0236] In one embodiment, the responding to the requesting
application/client on the device 250 is timed to correspond to a
manner in which the content server would have responded to the
outgoing request over a persistent connection (e.g., over the
persistent connection, or long-held HTTP connection, long poll type
connection, that would have been established absent interception by
the local proxy). The timing of the response can be emulated or
simulated by the local proxy 275 to preserve application behavior
such that end user experience is not affected, or minimally
affected by serving stored content from the local cache 285 rather
than fresh content received from the intended content source (e.g.,
content host/application server 110 of FIG. 1A-B). The timing can
be replicated exactly or estimated within a tolerance parameter,
which may go unnoticed by the user or treated similarly by the
application so as to not cause operation issues.
[0237] For example, the outgoing request can be a request for a
persistent connection intended for the content server (e.g.,
application server/content provider of examples of FIG. 1A-1B). In
a persistent connection (e.g., long poll, COMET-style push or any
other push simulation in asynchronous HTTP requests, long-held HTTP
request, HTTP streaming, or others) with a content source (server),
the connection is held for some time after a request is sent. The
connection can typically be persisted between the mobile device and
the server until content is available at the server to be sent to
the mobile device. Thus, there typically can be some delay in time
between when a long poll request is sent and when a response is
received from the content source. If a response is not provided by
the content source for a certain amount of time, the connection may
also terminate due to network reasons (e.g., socket closure) if a
response is not sent.
[0238] Thus, to emulate a response from a content server sent over
a persistent connection (e.g., a long poll style connection), the
manner of response of the content server can be simulated by
allowing a time interval to elapse before responding to the
outgoing request with the cached response. The length of the time
interval can be determined on a request by request basis or on an
application by application (client by client basis), for
example.
[0239] In one embodiment, the time interval is determined based on
request characteristics (e.g., timing characteristics) of an
application on the mobile device from which the outgoing request
originates. For example, poll request intervals (e.g., which can be
tracked, detected, and determined by the long poll detector 238a of
the poll interval detector 238) can be used to determine the time
interval to wait before responding to a request with a local cache
entry and managed by the response scheduler 249a.
[0240] One embodiment of the cache policy manager 245 includes a
poll schedule generator 247 which can generate a polling schedule
for one or more applications on the mobile device 250. The polling
schedule can specify a polling interval that can be employed by an
entity which is physically distinct and/or separate from the mobile
device 250 in monitoring the content source for one or more
applications (such that cached responses can be verified
periodically by polling a host server (host server 110 or 310) to
which the request is directed) on behalf of the mobile device. One
example of such an external entity which can monitor the content at
the source for the mobile device 250 is a proxy server (e.g., proxy
server 125 or 325 shown in the examples of FIG. 1B and FIG.
3A-C).
[0241] The polling schedule (e.g., including a rate/frequency of
polling) can be determined, for example, based on the interval
between the polling requests directed to the content source from
the mobile device. The polling schedule or rate of polling may be
determined at the mobile device 250 (by the local proxy). In one
embodiment, the poll interval detector 238 of the application
behavior detector 236 can monitor polling requests directed to a
content source from the mobile device 250 in order to determine an
interval between the polling requests made from any or all
application (e.g., mobile application).
[0242] For example, the poll interval detector 238 can track
requests and responses for applications or clients on the device
250. In one embodiment, consecutive requests are tracked prior to
detection of an outgoing request initiated from the application
(e.g., mobile application) on the mobile device 250 by the same
mobile client or application (e.g., mobile application). The
polling rate can be determined using request information collected
for the request for which the response is cached. In one
embodiment, the rate is determined from averages of time intervals
between previous requests generated by the same client which
generated the request. For example, a first interval may be
computed between the current request and a previous request, and a
second interval can be computed between the two previous requests.
The polling rate can be set from the average of the first interval
and the second interval and sent to the proxy server in setting up
the caching strategy.
[0243] Alternate intervals may be computed in generating an
average; for example, multiple previous requests in addition to two
previous requests may be used, and more than two intervals may be
used in computing an average. In general, in computing intervals, a
given request need not have resulted in a response to be received
from the host server/content source in order to use it for interval
computation. In other words, the timing characteristics of a given
request may be used in interval computation, as long as the request
has been detected, even if the request failed in sending, or if the
response retrieval failed.
[0244] One embodiment of the poll schedule generator 247 includes a
schedule update engine 247a and/or a time adjustment engine 247b.
The schedule update engine 247a can determine a need to update a
rate or polling interval with which a given application
server/content host from a previously set value, based on a
detected interval change in the actual requests generated from a
client or application (e.g., mobile application) on the mobile
device 250.
[0245] For example, a request for which a monitoring rate was
determined may now be sent from the application (e.g., mobile
application) or client at a different request interval. The
scheduled update engine 247a can determine the updated polling
interval of the actual requests and generate a new rate, different
from the previously set rate to poll the host at on behalf of the
mobile device 250. The updated polling rate can be communicated to
the remote proxy (proxy server 325) over the cellular network for
the remote proxy to monitor the given host. In some instances, the
updated polling rate may be determined at the remote proxy or
remote entity which monitors the host.
[0246] In one embodiment, the time adjustment engine 247b can
further optimize the poll schedule generated to monitor the
application server/content source (110 or 310). For example, the
time adjustment engine 247b can optionally specify a time to start
polling to the proxy server. For example, in addition to setting
the polling interval at which the proxy server is to monitor the
application, server/content host can also specify the time at which
an actual request was generated at the mobile
client/application.
[0247] However, in some cases, due to inherent transmission delay
or added network delays or other types of latencies, the remote
proxy server receives the poll setup from the local proxy with some
delay (e.g., a few minutes, or a few seconds). This has the effect
of detecting response change at the source after a request is
generated by the mobile client/application causing the invalidate
of the cached response to occur after it has once again been served
to the application after the response is no longer current or
valid. This discrepancy is further illustrated diagrammatically in
the data timing diagram of FIG. 21.
[0248] To resolve this non-optimal result of serving the out-dated
content once again before invalidating it, the time adjustment
engine 247b can specify the time (t0) at which polling should begin
in addition to the rate, where the specified initial time t0 can be
specified to the proxy server 325 as a time that is less than the
actual time when the request was generated by the mobile
app/client. This way, the server polls the resource slightly before
the generation of an actual request by the mobile client such that
any content change can be detected prior to an actual application
request. This prevents invalid or irrelevant out-dated
content/response from being served once again before fresh content
is served.
[0249] In one embodiment, an outgoing request from a mobile device
250 is detected to be for a persistent connection (e.g., a long
poll, COMET style push, and long-held (HTTP) request) based on
timing characteristics of prior requests from the same application
or client on the mobile device 250. For example, requests and/or
corresponding responses can be tracked by the request/response
tracking engine 238b of the long poll detector 238a of the poll
interval detector 238.
[0250] The timing characteristics of the consecutive requests can
be determined to set up a polling schedule for the application or
client. The polling schedule can be used to monitor the content
source (content source/application server) for content changes such
that cached content stored on the local cache in the mobile device
250 can be appropriately managed (e.g., updated or discarded). In
one embodiment, the timing characteristics can include, for
example, a response delay time (`D`) and/or an idle time
(`IT`).
[0251] In one embodiment, the response/request tracking engine 238b
can track requests and responses to determine, compute, and/or
estimate, the timing diagrams for applicant or client requests.
[0252] For example, the response/request tracking engine 238b
detects a first request (Request 0) initiated by a client on the
mobile device and a second request (Request 1) initiated by the
client on the mobile device after a response is received at the
mobile device responsive to the first request. The second request
is one that is subsequent to the first request.
[0253] In one embodiment, the response/request tracking engine 238b
can track requests and responses to determine, compute, and/or
estimate the timing diagrams for applicant or client requests. The
response/request tracking engine 238b can detect a first request
initiated by a client on the mobile device and a second request
initiated by the client on the mobile device after a response is
received at the mobile device responsive to the first request. The
second request is one that is subsequent to the first request.
[0254] The response/request tracking engine 238b further determines
relative timings between the first, second requests, and the
response received in response to the first request. In general, the
relative timings can be used by the long poll detector 238a to
determine whether requests generated by the application are long
poll requests.
[0255] Note that in general, the first and second requests that are
used by the response/request tracking engine 238b in computing the
relative timings are selected for use after a long poll hunting
period has settled or in the event when long poll hunting does not
occur.
[0256] In one embodiment, the long poll hunting detector 238c can
identify or detect hunting mode, by identifying increasing request
intervals (e.g., increasing delays). The long poll hunting detector
238a can also detect hunting mode by detecting increasing request
intervals, followed by a request with no response (e.g., connection
timed out), or by detecting increasing request intervals followed
by a decrease in the interval. In addition, the long poll hunting
detector 238c can apply a filter value or a threshold value to
request-response time delay value (e.g., an absolute value) above
which the detected delay can be considered to be a long poll
request-response delay. The filter value can be any suitable value
characteristic of long polls and/or network conditions (e.g., 2 s,
5 s, 10 s, 15 s, 20 s., etc.) and can be used as a filter or
threshold value.
[0257] The response delay time (`D`) refers to the start time to
receive a response after a request has been sent and the idle
refers to time to send a subsequent request after the response has
been received. In one embodiment, the outgoing request is detected
to be for a persistent connection based on a comparison (e.g.,
performed by the tracking engine 238b) of the response delay time
relative (`D`) or average of (`D`) (e.g., any average over any
period of time) to the idle time (`IT`), for example, by the long
poll detector 238a. The number of averages used can be fixed,
dynamically adjusted, or changed over a longer period of time. For
example, the requests initiated by the client are determined to be
long poll requests if the response delay time interval is greater
than the idle time interval (D>IT or D>>IT). In one
embodiment, the tracking engine 238b of the long poll detector
computes, determines, or estimates the response delay time interval
as the amount of time elapsed between time of the first request and
initial detection or full receipt of the response.
[0258] In one embodiment, a request is detected to be for a
persistent connection when the idle time (`IT`) is short since
persistent connections, established in response to long poll
requests or long poll HTTP requests for example, can also be
characterized in detecting immediate or near-immediate issuance of
a subsequent request after receipt of a response to a previous
request (e.g., IT.about.0). As such, the idle time (`IT`) can also
be used to detect such immediate or near-immediate re-request to
identify long poll requests. The absolute or relative timings
determined by the tracking engine 238b are used to determine
whether the second request is immediately or near-immediately
re-requested after the response to the first request is received.
For example, a request may be categorized as a long poll request if
D+RT+IT D+RT since IT is small for this to hold true. IT may be
determined to be small if it is less than a threshold value. Note
that the threshold value could be fixed or calculated over a
limited time period (a session, a day, a month, etc.), or
calculated over a longer time period (e.g., several months or the
life of the analysis). For example, for every request, the average
IT can be determined, and the threshold can be determined using
this average IT (e.g., the average IT less a certain percentage may
be used as the threshold). This can allow the threshold to
automatically adapt over time to network conditions and changes in
server capability, resource availability or server response. A
fixed threshold can take upon any value including by way of example
but not limitation (e.g., 1 s. 2 s. 3 s . . . etc.).
[0259] In one embodiment, the long poll detector 238a can compare
the relative timings (e.g., determined by the tracker engine 238b)
to request-response timing characteristics for other applications
to determine whether the requests of the application are long poll
requests. For example, the requests initiated by a client or
application can be determined to be long poll requests if the
response delay interval time (`D`) or the average response delay
interval time (e.g., averaged over x number of requests or any
number of delay interval times averaged over x amount of time) is
greater than a threshold value.
[0260] The threshold value can be determined using response delay
interval times for requests generated by other clients, for example
by the request/response tracking engine 238b and/or by the
application profile generator 239 (e.g., the response delay
interval tracker 239a). The other clients may reside on the same
mobile device and the threshold value is determined locally by
components on the mobile device. The threshold value can be
determined for all requests over all resources server over all
networks, for example. The threshold value can be set to a specific
constant value (e.g., 30 seconds, for example) to be used for all
requests, or any request which does not have an applicable
threshold value (e.g., long poll is detected if D>30
seconds).
[0261] In some instances, the other clients reside on different
mobile devices and the threshold can be determined by a proxy
server (e.g., proxy server 325 of the host 300 shown in the example
of FIG. 3A-B) which is external to the mobile device and able to
communicate over a wireless network with the multiple different
mobile devices, as will be further described with reference to FIG.
3B.
[0262] In one embodiment, the cache policy manager 245 sends the
polling schedule to the proxy server (e.g., proxy server 125 or 325
shown in the examples of FIG. 1B and FIG. 3A) and can be used by
the proxy server in monitoring the content source, for example, for
changed or new content (updated response different from the cached
response associated with a request or application). A polling
schedule sent to the proxy can include multiple timing parameters
including but not limited to interval (time from request 1 to
request 2) or a time out interval (time to wait for response, used
in long polls, for example). The timing intervals `RI`, `D`, `RT`,
and/or `IT`, or some statistical manipulation of the above values
(e.g., average, standard deviation, etc.) may all or in part be
sent to the proxy server.
[0263] For example, in the case when the local proxy 275 detects a
long poll, the various timing intervals in a request/response
timing sequence (e.g., `D`, `RT`, and/or `IT`) can be sent to the
proxy server 325 for use in polling the content source (e.g.,
application server/content host 110). The local proxy 275 can also
identify to the proxy server 325 that a given application or
request to be monitored is a long poll request (e.g., instructing
the proxy server to set a `long poll flag`, for example). In
addition, the proxy server uses the various timing intervals to
determine when to send keep-alive indications on behalf of mobile
devices.
[0264] The local cache invalidator 244 of the caching policy
manager 245 can invalidate cache elements in the local cache (e.g.,
cache 185 or 285) when new or changed data (e.g., updated response)
is detected from the application server/content source for a given
request. The cached response can be determined to be invalid for
the outgoing request based on a notification received from the
proxy server (e.g., proxy 325 or the host server 300). The source
which provides responses to requests of the mobile client can be
monitored to determine relevancy of the cached response stored in
the cache of the mobile device 250 for the request. For example,
the cache invalidator 244 can further remove/delete the cached
response from the cache of the mobile device when the cached
response is no longer valid for a given request or a given
application.
[0265] In one embodiment, the cached response is removed from the
cache after it is provided once again to an application which
generated the outgoing request after determining that the cached
response is no longer valid. The cached response can be provided
again without waiting for the time interval or provided again after
waiting for a time interval (e.g., the time interval determined to
be specific to emulate the response delay in a long poll). In one
embodiment, the time interval is the response delay `D` or an
average value of the response delay `D` over two or more
values.
[0266] The new or changed data can be, for example, detected by the
proxy server (e.g., proxy server 125 or 325 shown in the examples
of FIG. 1B and FIG. 3A). When a cache entry for a given
request/poll has been invalidated, the use of the radio on the
mobile device 250 can be enabled (e.g., by the local proxy 275 or
the cache policy manager 245) to satisfy the subsequent polling
requests, as further described with reference to the interaction
diagram of FIG. 4B.
[0267] One embodiment of the cache policy manager 245 includes a
cache or connect selection engine 249 which can decide whether to
use a locally cached entry to satisfy a poll/content request
generated at the mobile device 250 by an application or widget. For
example, the local proxy 275 or the cache policy manger 245 can
intercept a polling request, made by an application (e.g., mobile
application) on the mobile device, to contact the application
server/content provider. The selection engine 249 can determine
whether the content received for the intercepted request has been
locally stored as cache elements for deciding whether the radio of
the mobile device needs to be activated to satisfy the request made
by the application (e.g., mobile application) and also determine
whether the cached response is still valid for the outgoing request
prior to responding to the outgoing request using the cached
response.
[0268] In one embodiment, the local proxy 275, in response to
determining that relevant cached content exists and is still valid,
can retrieve the cached elements from the local cache to provide a
response to the application (e.g., mobile application) which made
the polling request such that a radio of the mobile device is not
activated to provide the response to the application (e.g., mobile
application). In general, the local proxy 275 continues to provide
the cached response each time the outgoing request is received
until the updated response different from the cached response is
detected.
[0269] When it is determined that the cached response is no longer
valid, a new request for a given request is transmitted over the
wireless network for an updated response. The request can be
transmitted to the application server/content provider (e.g.,
server/host 110) or the proxy server on the host server (e.g.,
proxy 325 on the host 300) for a new and updated response. In one
embodiment the cached response can be provided again as a response
to the outgoing request if a new response is not received within
the time interval, prior to removal of the cached response from the
cache on the mobile device.
[0270] FIG. 2C depicts a block diagram illustrating another example
of components in the application behavior detector 236 and the
caching policy manager 245 in the local proxy 275 on the
client-side of the distributed proxy system shown in the example of
FIG. 2A. The illustrated application behavior detector 236 and the
caching policy manager 245 can, for example, enable the local proxy
275 to detect cache defeat and perform caching of content addressed
by identifiers intended to defeat cache.
[0271] In one embodiment, the caching policy manager 245 includes a
cache defeat resolution engine 221, an identifier formalizer 211, a
cache appropriateness decision engine 246, a poll schedule
generator 247, an application protocol module 248, a cache or
connect selection engine 249 having a cache query module 229,
and/or a local cache invalidator 244. The cache defeat resolution
engine 221 can further include a pattern extraction module 222
and/or a cache defeat parameter detector 223. The cache defeat
parameter detector 223 can further include a random parameter
detector 224 and/or a time/date parameter detector 226. One
embodiment further includes an application cache policy repository
243 coupled to the decision engine 246.
[0272] In one embodiment, the application behavior detector 236
includes a pattern detector 237, a poll interval detector 238, an
application profile generator 239, and/or a priority engine 241.
The pattern detector 237 can further include a cache defeat
parameter detector 223 having also, for example, a random parameter
detector 233 and/or a time/date parameter detector 234. One
embodiment further includes an application profile repository 242
coupled to the application profile generator 239. The application
profile generator 239, and the priority engine 241 have been
described in association with the description of the application
behavior detector 236 in the example of FIG. 2A.
[0273] The cache defeat resolution engine 221 can detect, identify,
track, manage, and/or monitor content or content sources (e.g.,
servers or hosts) which employ identifiers and/or are addressed by
identifiers (e.g., resource identifiers such as URLs and/or URIs)
with one or more mechanisms that defeat cache or are intended to
defeat cache. The cache defeat resolution engine 221 can, for
example, detect from a given data request generated by an
application or client that the identifier defeats or potentially
defeats cache, where the data request otherwise addresses content
or responses from a host or server (e.g., application
server/content host 110 or 310) that is cacheable.
[0274] In one embodiment, the cache defeat resolution engine 221
detects or identifies cache defeat mechanisms used by content
sources (e.g., application server/content host 110 or 310) using
the identifier of a data request detected at the mobile device 250.
The cache defeat resolution engine 221 can detect or identify a
parameter in the identifier which can indicate that cache defeat
mechanism is used. For example, a format, syntax, or pattern of the
parameter can be used to identify cache defeat (e.g., a pattern,
format, or syntax as determined or extracted by the pattern
extraction module 222).
[0275] The pattern extraction module 222 can parse an identifier
into multiple parameters or components and perform a matching
algorithm on each parameter to identify any of which match one or
more predetermined formats (e.g., a date and/or time format, as
illustrated in parameters 702 shown in FIG. 7). For example, the
results of the matching or the parsed out parameters from an
identifier can be used (e.g., by the cache defeat parameter
detector 223) to identify cache defeating parameters which can
include one or more changing parameters.
[0276] The cache defeat parameter detector 223, in one embodiment
can detect random parameters (e.g., by the random parameter
detector 224) and/or time and/or date parameters which are
typically used for cache defeat. The cache defeat parameter
detector 223 can detect random parameters (e.g., as illustrated in
parameters 752 shown in FIG. 7) and/or time/dates using commonly
employed formats for these parameters and performing pattern
matching algorithms and tests.
[0277] In addition to detecting patterns, formats, and/or syntaxes,
the cache defeat parameter detector 223 further determines or
confirms whether a given parameter is defeating cache and whether
the addressed content can be cached by the distributed caching
system. The cache defeat parameter detector 223 can detect this by
analyzing responses received for the identifiers utilized by a
given data request. In general, a changing parameter in the
identifier is identified to indicate cache defeat when responses
corresponding to multiple data requests are the same even when the
multiple data requests uses identifiers with the changing parameter
being different for each of the multiple data requests.
[0278] For example, at least two same responses may be required to
identify the changing parameter as indicating cache defeat. In some
instances, at least three same responses may be required. The
requirement for the number of same responses needed to determine
that a given parameter with a varying value between requests is
cache defeating may be application specific, context dependent,
and/or user dependent/user specified, or a combination of the
above. Such a requirement may also be static or dynamically
adjusted by the distributed cache system to meet certain
performance thresholds and/or either explicit/implicit feedback
regarding user experience (e.g., whether the user or application is
receiving relevant/fresh content responsive to requests). More of
the same responses may be required to confirm cache defeat, or for
the system to treat a given parameter as intended for cache defeat
if an application begins to malfunction due to response caching
and/or if the user expresses dissatisfaction (explicit user
feedback) or the system detects user frustration (implicit user
cues).
[0279] The cache appropriateness decision engine 246 can detect,
assess, or determine whether content from a content source (e.g.,
application server/content provider 110 in the example of FIG. 1B)
with which a mobile device 250 interacts, has content that may be
suitable for caching. In some instances, content from a given
application server/content provider (e.g., the server/provider 110
of FIG. 1B) is determined to be suitable for caching based on a set
of criteria (for example, criteria specifying time criticality of
the content that is being requested from the content source). In
one embodiment, the local proxy (e.g., the local proxy 175 or 275
of FIG. 1B and FIG. 2A) applies a selection criteria to store the
content from the host server which is requested by an application
as cached elements in a local cache on the mobile device to satisfy
subsequent requests made by the application.
[0280] The selection criteria can also include, by way of example,
but not limitation, state of the mobile device indicating whether
the mobile device is active or inactive, network conditions, and/or
radio coverage statistics. The cache appropriateness decision
engine 246 can any one or any combination of the criteria, and in
any order, in identifying sources for which caching may be
suitable.
[0281] Once application servers/content providers having identified
or detected content that is potentially suitable for local caching
on the mobile device 250, the cache policy manager 245 can proceed
to cache the associated content received from the identified
sources by storing content received from the content source as
cache elements in a local cache (e.g., local cache 185 or 285 shown
in the examples of FIG. 1B and FIG. 2A, respectively) on the mobile
device 250. The content source can also be identified to a proxy
server (e.g., proxy server 125 or 325 shown in the examples of FIG.
1B and FIG. 3A, respectively) remote from and in wireless
communication with the mobile device 250 such that the proxy server
can monitor the content source (e.g., application server/content
provider 110) for new or changed data. Similarly, the local proxy
(e.g., the local proxy 175 or 275 of FIG. 1B and FIG. 2A,
respectively) can identify to the proxy server that content
received from a specific application server/content provider is
being stored as cached elements in the local cache.
[0282] In one embodiment, cache elements are stored in the local
cache 285 as being associated with a normalized version of an
identifier for an identifier employing one or more parameters
intended to defeat cache. The identifier can be normalized by the
identifier normalizer module 211 and the normalization process can
include, by way of example, one or more of: converting the URI
scheme and host to lower-case, capitalizing letters in
percent-encoded escape sequences, removing a default port, and
removing duplicate slashes.
[0283] In another embodiment, the identifier is normalized by
removing the parameter for cache defeat and/or replacing the
parameter with a static value which can be used to address or be
associated with the cached response received responsive to a
request utilizing the identifier by the normalizer 211 or the cache
defeat parameter handler 212. For example, the cached elements
stored in the local cache 285 (shown in FIG. 2A) can be identified
using the normalized version of the identifier or a hash value of
the normalized version of the identifier. The hash value of an
identifier or of the normalized identifier may be generated by the
hash engine 213.
[0284] Once content has been locally cached, the cache policy
manager 245 can, upon receiving future polling requests to contact
the content server, retrieve the cached elements from the local
cache to respond to the polling request made at the mobile device
250 such that a radio of the mobile device is not activated to
service the polling request. Such servicing and fulfilling
application (e.g., mobile application) requests locally via local
cache entries allow for more efficient resource and mobile network
traffic utilization and management since network bandwidth and
other resources need not be used to request/receive poll responses
which may have not changed from a response that has already been
received at the mobile device 250.
[0285] One embodiment of the cache policy manager 245 includes a
poll schedule generator 247 which can generate a polling schedule
for one or more applications on the mobile device 250. The polling
schedule can specify a polling interval that can be employed by the
proxy server (e.g., proxy server 125 or 325 shown in the examples
of FIG. 1B and FIG. 3A) in monitoring the content source for one or
more applications. The polling schedule can be determined, for
example, based on the interval between the polling requests
directed to the content source from the mobile device. In one
embodiment, the poll interval detector 238 of the application
behavior detector can monitor polling requests directed to a
content source from the mobile device 250 in order to determine an
interval between the polling requests made from any or all
application (e.g., mobile application).
[0286] In one embodiment, the cache policy manager 245 sends the
polling schedule is sent to the proxy server (e.g., proxy server
125 or 325 shown in the examples of FIG. 1B and FIG. 3A) and can be
used by the proxy server in monitoring the content source, for
example, for changed or new content. The local cache invalidator
244 of the caching policy manager 245 can invalidate cache elements
in the local cache (e.g., cache 185 or 285) when new or changed
data is detected from the application server/content source for a
given request. The new or changed data can be, for example,
detected by the proxy server. When a cache entry for a given
request/poll has been invalidated and/or removed (e.g., deleted
from cache) after invalidation, the use of the radio on the mobile
device 250 can be enabled (e.g., by the local proxy or the cache
policy manager 245) to satisfy the subsequent polling requests, as
further described with reference to the interaction diagram of FIG.
4B.
[0287] In another embodiment, the proxy server (e.g., proxy server
125 or 325 shown in the examples of FIG. 1B and FIG. 3A) uses a
modified version of a resource identifier used in a data request to
monitor a given content source (the application server/content host
110 of FIG. 1A and FIG. 1B to which the data request is addressed)
for new or changed data. For example, in the instance where the
content source or identifier is detected to employ cache defeat
mechanisms, a modified (e.g., normalized) identifier can be used
instead to poll the content source. The modified or normalized
version of the identifier can be communicated to the proxy server
by the caching policy manager 245, or more specifically the cache
defeat parameter handler 212 of the identifier normalizer 211.
[0288] The modified identifier used by the proxy server to poll the
content source on behalf of the mobile device/application (e.g.,
mobile application) may or may not be the same as the normalized
identifier. For example, the normalized identifier may be the
original identifier with the changing cache defeating parameter
removed whereas the modified identifier uses a substitute parameter
in place of the parameter that is used to defeat cache (e.g., the
changing parameter replaced with a static value or other
predetermined value known to the local proxy and/or proxy server).
The modified parameter can be determined by the local proxy 275 and
communicated to the proxy server. The modified parameter may also
be generated by the proxy server (e.g., by the identifier modifier
module 353 shown in the example of FIG. 3C).
[0289] One embodiment of the cache policy manager 245 includes a
cache or connect selection engine 249 which can decide whether to
use a locally cached entry to satisfy a poll/content request
generated at the mobile device 250 by an application or widget. For
example, the local proxy 275 or the cache policy manger 245 can
intercept a polling request made by an application (e.g., mobile
application) on the mobile device, to contact the application
server/content provider. The selection engine 249 can determine
whether the content received for the intercepted request has been
locally stored as cache elements for deciding whether the a radio
of the mobile device needs to be activated to satisfy the request
made by the application (e.g., mobile application). In one
embodiment, the local proxy 275, in response to determining that
relevant cached content exists and is still valid, can retrieve the
cached elements from the local cache to provide a response to the
application (e.g., mobile application) which made the polling
request such that a radio of the mobile device is not activated to
provide the response to the application (e.g., mobile
application).
[0290] In one embodiment, the cached elements stored in the local
cache 285 (shown in FIG. 2A) can be identified using a normalized
version of the identifier or a hash value of the normalized version
of the identifier, for example, using the cache query module 229.
Cached elements can be stored with normalized identifiers which
have cache defeating parameters removed or otherwise replaced such
that the relevant cached elements can be identified and retrieved
in the future to satisfy other requests employing the same type of
cache defeat. For example, when an identifier utilized in a
subsequent request is determined to be utilizing the same cache
defeating parameter, the normalized version of this identifier can
be generated and used to identify a cached response stored in the
mobile device cache to satisfy the data request. The hash value of
an identifier or of the normalized identifier may be generated by
the hash engine 213 of the identifier normalizer 211.
[0291] FIG. 2D depicts a block diagram illustrating examples of
additional components in the local proxy 275 shown in the example
of FIG. 2A which is further capable of performing mobile traffic
categorization and policy implementation based on application
behavior and/or user activity.
[0292] In this embodiment of the local proxy 275, the user activity
module 215 further includes one or more of, a user activity tracker
215a, a user activity prediction engine 215b, and/or a user
expectation manager 215c. The application behavior detect 236 can
further include a prioritization engine 241a, a time criticality
detection engine 241b, an application state categorizer 241c,
and/or an application traffic categorizer 241d. The local proxy 275
can further include a backlight detector 219 and/or a network
configuration selection engine 251. The network configuration
selection engine 251 can further include, one or more of, a
wireless generation standard selector 251a, a data rate specifier
251b, an access channel selection engine 251c, and/or an access
point selector.
[0293] In one embodiment, the application behavior detector 236 is
able to detect, determined, identify, or infer, the activity state
of an application on the mobile device 250 to which traffic has
originated from or is directed to, for example, via the application
state categorizer 241c and/or the traffic categorizer 241d. The
activity state can be determined by whether the application is in a
foreground or background state on the mobile device (via the
application state categorizer 241c) since the traffic for a
foreground application vs. a background application may be handled
differently.
[0294] In one embodiment, the activity state can be determined,
detected, identified, or inferred with a level of certainty of
heuristics, based on the backlight status of the mobile device 250
(e.g., by the backlight detector 219) or other software agents or
hardware sensors on the mobile device, including but not limited
to, resistive sensors, capacitive sensors, ambient light sensors,
motion sensors, touch sensors, etc. In general, if the backlight is
on, the traffic can be treated as being or determined to be
generated from an application that is active or in the foreground,
or the traffic is interactive. In addition, if the backlight is on,
the traffic can be treated as being or determined to be traffic
from user interaction or user activity, or traffic containing data
that the user is expecting within some time frame.
[0295] In one embodiment, the activity state is determined based on
whether the traffic is interactive traffic or maintenance traffic.
Interactive traffic can include transactions from responses and
requests generated directly from user activity/interaction with an
application and can include content or data that a user is waiting
or expecting to receive. Maintenance traffic may be used to support
the functionality of an application which is not directly detected
by a user. Maintenance traffic can also include actions or
transactions that may take place in response to a user action, but
the user is not actively waiting for or expecting a response.
[0296] For example, a mail or message delete action at a mobile
device 250 generates a request to delete the corresponding mail or
message at the server, but the user typically is not waiting for a
response. Thus, such a request may be categorized as maintenance
traffic, or traffic having a lower priority (e.g., by the
prioritization engine 241a) and/or is not time-critical (e.g., by
the time criticality detection engine 214b).
[0297] Contrastingly, a mail `read` or message `read` request
initiated by a user a the mobile device 250, can be categorized as
`interactive traffic` since the user generally is waiting to access
content or data when they request to read a message or mail.
Similarly, such a request can be categorized as having higher
priority (e.g., by the prioritization engine 241a) and/or as being
time critical/time sensitive (e.g., by the time criticality
detection engine 241b).
[0298] The time criticality detection engine 241b can generally
determine, identify, infer the time sensitivity of data contained
in traffic sent from the mobile device 250 or to the mobile device
from a host server (e.g., host 300) or application server (e.g.,
app server/content source 110). For example, time sensitive data
can include, status updates, stock information updates, IM presence
information, email messages or other messages, actions generated
from mobile gaming applications, webpage requests, location
updates, etc. Data that is not time sensitive or time critical, by
nature of the content or request, can include requests to delete
messages, mark-as-read or edited actions, application-specific
actions such as a add-friend or delete-friend request, certain
types of messages, or other information which does not frequently
changing by nature, etc. In some instances when the data is not
time critical, the timing with which to allow the traffic to pass
through is set based on when additional data needs to be sent from
the mobile device 250. For example, traffic shaping engine 255 can
align the traffic with one or more subsequent transactions to be
sent together in a single power-on event of the mobile device radio
(e.g, using the alignment module 256 and/or the batching module
257). The alignment module 256 can also align polling requests
occurring close in time directed to the same host server, since
these request are likely to be responded to with the same data.
[0299] In the alternate or in combination, the activity state can
be determined from assessing, determining, evaluating, inferring,
identifying user activity at the mobile device 250 (e.g., via the
user activity module 215). For example, user activity can be
directly detected and tracked using the user activity tracker 215a.
The traffic resulting therefrom can then be categorized
appropriately for subsequent processing to determine the policy for
handling. Furthermore, user activity can be predicted or
anticipated by the user activity prediction engine 215b. By
predicting user activity or anticipating user activity, the traffic
thus occurring after the prediction can be treated as resulting
from user activity and categorized appropriately to determine the
transmission policy.
[0300] In addition, the user activity module 215 can also manage
user expectations (e.g., via the user expectation manager 215c
and/or in conjunction with the activity tracker 215 and/or the
prediction engine 215b) to ensure that traffic is categorized
appropriately such that user expectations are generally met. For
example, a user-initiated action should be analyzed (e.g., by the
expectation manager 215) to determine or infer whether the user
would be waiting for a response. If so, such traffic should be
handled under a policy such that the user does not experience an
unpleasant delay in receiving such a response or action.
[0301] In one embodiment, an advanced generation wireless standard
network is selected for use in sending traffic between a mobile
device and a host server in the wireless network based on the
activity state of the application on the mobile device for which
traffic is originated from or directed to. An advanced technology
standards such as the 3G, 3.5G, 3G+, 4G, or LTE network can be
selected for handling traffic generated as a result of user
interaction, user activity, or traffic containing data that the
user is expecting or waiting for. Advanced generation wireless
standard network can also be selected for to transmit data
contained in traffic directed to the mobile device which responds
to foreground activities.
[0302] In categorizing traffic and defining a transmission policy
for mobile traffic, a network configuration can be selected for use
(e.g., by the network configuration selection engine 251) on the
mobile device 250 in sending traffic between the mobile device and
a proxy server (325) and/or an application server (e.g., app
server/host 110). The network configuration that is selected can be
determined based on information gathered by the application
behavior module 236 regarding application activity state (e.g.,
background or foreground traffic), application traffic category
(e.g., interactive or maintenance traffic), any priorities of the
data/content, time sensitivity/criticality.
[0303] The network configuration selection engine 251 can select or
specify one or more of, a generation standard (e.g., via wireless
generation standard selector 251a), a data rate (e.g., via data
rate specifier 251b), an access channel (e.g., access channel
selection engine 251c), and/or an access point (e.g., vai the
access point selector 251d), in any combination.
[0304] For example, a more advanced generation (e.g, 3G, LTE, or 4G
or later) can be selected or specified for traffic when the
activity state is in interaction with a user or in a foreground on
the mobile device. Contrastingly, an older generation standard
(e.g., 2G, 2.5G, or 3G or older) can be specified for traffic when
one or more of the following is detected, the application is not
interacting with the user, the application is running in the
background on the mobile device, or the data contained in the
traffic is not time critical, or is otherwise determined to have
lower priority.
[0305] Similarly, a network configuration with a slower data rate
can be specified for traffic when one or more of the following is
detected, the application is not interacting with the user, the
application is running in the background on the mobile device, or
the data contained in the traffic is not time critical. The access
channel (e.g., Forward access channel or dedicated channel) can be
specified.
[0306] FIG. 2E depicts a block diagram illustrating examples of
additional components in the traffic shaping engine 255 and the
application behavior detector 236 shown in the example of FIG. 2A
which are further capable of facilitating alignment of incoming
data transfer to a mobile or broadband device, or its user, to
optimize the number of connections that need to be established for
receiving data over the wireless network or broadband network.
[0307] In one embodiment of the local proxy 275, the traffic
shaping engine 255, in addition to the alignment module 256,
batching module 257, further includes a poll interval adjuster 258.
The poll interval adjuster 258 can include a factor or denominator
detection engine 258a, a critical application detector 258b, a
critical interval identifier 258c, and/or a polling interval
setting engine 258d. Further in one embodiment, the application
behavior detector 236 of the local proxy 275 further includes a
poll interval detector 238.
[0308] In facilitating alignment of data bursts across various
services or hosts to the mobile device 250, the local proxy 275 can
initially determine, detect, identify, compute, infer, extract the
an original or default polling interval for applications or mobile
clients on the mobile device 250 (e.g., by the poll interval
detector 238). The original or default polling interval is
typically that characteristic of the mobile application itself
and/or its host (e.g., its corresponding application server/content
host 110 shown in FIG. 1A-1B). The poll interval detector 238 can
detect the original or default poll interval for any number or all
of the mobile applications which regularly poll their application
servers or hosts for use by the proxy 275 in generating or
adjusting the polling intervals suitable for use for the device 250
based on the applications installed thereon and their respective
poll timing characteristics.
[0309] For example, the poll intervals (original or default) of the
mobile clients or applications on device 250 can be used by the
poll interval adjuster 258. In general, an adjusted polling
interval for a first service is generated based on a polling
interval of a second service, which may be serviced by a distinct
host from the first service (e.g., Twitter=service 1;
ESPN.com=service 2). The adjusted polling interval computed for the
first service and/or the second service, can be used in aligning at
least some traffic received from the distinct hosts due to access
on a mobile device of first and second services.
[0310] For example, in one embodiment, the adjusted polling
interval of the first service can be a factor or denominator that
the original polling interval of the first service has in common
with the original polling interval of the second service (e.g., as
determined by the factor or denominator detection engine 258a), and
can further be determined based on an original polling interval of
the first service. Note that the adjusted polling interval of the
first service need not be different from the original polling
interval of the first service when the original polling interval of
the first service and the polling interval of the second service
are factors or denominators of each other.
[0311] In one embodiment, the detection engine 258a is able to
further determine multiples of a factor or denominator of the
polling interval of the second service and the adjusted polling
interval of the first service is a multiple of a factor or a
multiple of a denominator of the polling interval of the second
service. In addition, the engine 258a can determine multiples of a
common factor or a common denominator of a majority number of the
default polling intervals for multiple applications on the device
250.
[0312] In addition, the adjusted polling interval of the first
service can be further determined, adjusted, or reconfigured (e.g.,
by the polling interval setting engine 258d), based on time
criticality of traffic from the first service relative to time
criticality of traffic from the second service, or additional
services on the mobile device 250. For example, the critical
application detector 258b can identify, detect, or receive input
identifying or specifying one or more applications on the device
250 as being more critical than others (e.g., higher priority, time
sensitive content/traffic, user preferred application, OS sponsored
application, operator-sponsored content, etc.) and further adjust
the polling intervals of the first and/or second services if
need.
[0313] For example, the critical application detector 258b can
identify a critical application as being the most time critical of
all applications on the mobile device, or a set of applications for
which data burst alignment is being applied or attempted on. For
the critical application (s), the polling interval of the critical
application is identified as a minimum critical interval (e.g., by
the critical interval identifier 258c), which is not to be exceeded
in assigning an updated polling interval for the critical
application such that the priority in data needs (e.g., whether it
is a user-need, device-need, or application-need) for prompt and
timely delivery of data from the application server or content
host.
[0314] High priority information/data or application can include,
for example, financial data, sporting data or other data constantly
changing in nature, any data whose previous values have little to
no relevancy, any data (e.g., subscriptions or feeds) that a user
wishes to be immediately notified of in real time or near real
time, any specific feature indicated as a real time or near real
time feature by the application server/content host (e.g.,
real-time status updates, or real-time notifications, high priority
email or other messages, IM messages, etc.) or applications
servicing any type of high priority/time sensitive content.
[0315] Once the polling intervals of one or more applications on
the mobile device 250 have been set, the local proxy 275
communicates a polling schedule including the adjusted polling
interval (s) to a proxy server (eg., remote proxy 325 of FIG.
3A-3E) for use in aligning, in time, at least some traffic received
from the distinct hosts due to access on the mobile device of first
and second services, and any additional services.
[0316] In one embodiment, the poll interval setting engine 258d
also selecting a common starting point in time for an initial poll
of the content hosts servicing the multiple applications. The poll
interval setting engine 258d can set the start time to be anchored
to the same absolute point in time across the multiple applications
on the device 250. In general, the application servers/content
hosts are typically in UTC and use NTP to stay at the same time.
For example, the interval setting engine 258d can pick any minute
mark, second mark, hour mark, or other time indicators, and
communicate this to the remote proxy server (e.g., proxy 325) as
part of the adjusted polling parameter. The mark can be selected
randomly used by all applications as the common `initial time
t0."
[0317] Note that while the above description uses an example of two
applications, the same process can be performed for any number of
applications or all applications/clients on the mobile device 250.
In some instances, some or all of the functions performed by one or
more of the components poll interval adjustor 258 can be performed
remotely, for example, at a remote proxy server (e.g., proxy 325)
using the poll intervals detected locally at the mobile device 250
(e.g., by the poll interval detector 238). Note that the remote
proxy (e.g., proxy 325) can receive poll intervals for applications
across multiple devices and track adjusted intervals for
applications on multiple devices, as will be further described with
the example of FIG. 3E.
[0318] FIG. 3A depicts a block diagram illustrating an example of
server-side components in a distributed proxy and cache system
residing on a host server 300 that manages traffic in a wireless
network for resource conservation. The server-side proxy (or proxy
server 325) can further categorize mobile traffic and/or implement
delivery policies based on application behavior, content priority,
user activity, and/or user expectations.
[0319] The host server 300 generally includes, for example, a
network interface 308 and/or one or more repositories 312, 314, and
316. Note that server 300 may be any portable/mobile or
non-portable device, server, cluster of computers and/or other
types of processing units (e.g., any number of a machine shown in
the example of FIG. 11) able to receive or transmit signals to
satisfy data requests over a network including any wired or
wireless networks (e.g., WiFi, cellular, Bluetooth, etc.).
[0320] The network interface 308 can include networking module(s)
or devices(s) that enable the server 300 to mediate data in a
network with an entity that is external to the host server 300,
through any known and/or convenient communications protocol
supported by the host and the external entity. Specifically, the
network interface 308 allows the server 300 to communicate with
multiple devices including mobile phone devices 350 and/or one or
more application servers/content providers 310.
[0321] The host server 300 can store information about connections
(e.g., network characteristics, conditions, types of connections,
etc.) with devices in the connection metadata repository 312.
Additionally, any information about third party application or
content providers can also be stored in the repository 312. The
host server 300 can store information about devices (e.g., hardware
capability, properties, device settings, device language, network
capability, manufacturer, device model, OS, OS version, etc.) in
the device information repository 314. Additionally, the host
server 300 can store information about network providers and the
various network service areas in the network service provider
repository 316.
[0322] The communication enabled by network interface 308 allows
for simultaneous connections (e.g., including cellular connections)
with devices 350 and/or connections (e.g., including
wired/wireless, HTTP, Internet connections, LAN, WiFi, etc.) with
content servers/providers 310 to manage the traffic between devices
350 and content providers 310, for optimizing network resource
utilization and/or to conserver power (battery) consumption on the
serviced devices 350. The host server 300 can communicate with
mobile devices 350 serviced by different network service providers
and/or in the same/different network service areas. The host server
300 can operate and is compatible with devices 350 with varying
types or levels of mobile capabilities, including by way of example
but not limitation, 1G, 2G, 2G transitional (2.5G, 2.75G), 3G
(IMT-2000), 3G transitional (3.5G, 3.75G, 3.9G), 4G (IMT-advanced),
etc.
[0323] In general, the network interface 308 can include one or
more of a network adaptor card, a wireless network interface card
(e.g., SMS interface, WiFi interface, interfaces for various
generations of mobile communication standards including but not
limited to 1G, 2G, 3G, 3.5G, 4G type networks such as LTE, WiMAX,
etc.), Bluetooth, WiFi, or any other network whether or not
connected via a router, an access point, a wireless router, a
switch, a multilayer switch, a protocol converter, a gateway, a
bridge, a bridge router, a hub, a digital media receiver, and/or a
repeater.
[0324] The host server 300 can further include server-side
components of the distributed proxy and cache system which can
include a proxy server 325 and a server cache 335. In one
embodiment, the proxy server 325 can include an HTTP access engine
345, a caching policy manager 355, a proxy controller 365, a
traffic shaping engine 375, a new data detector 347 and/or a
connection manager 395.
[0325] The HTTP access engine 345 may further include a heartbeat
manager 398; the proxy controller 365 may further include a data
invalidator module 368; the traffic shaping engine 375 may further
include a control protocol 376 and a batching module 377.
Additional or less components/modules/engines can be included in
the proxy server 325 and each illustrated component.
[0326] As used herein, a "module," a "manager," a "handler," a
"detector," an "interface," a "controller," a "normalizer," a
"generator," an "invalidator," or an "engine" includes a general
purpose, dedicated or shared processor and, typically, firmware or
software modules that are executed by the processor. Depending upon
implementation-specific or other considerations, the module,
manager, handler, detector, interface, controller, normalizer,
generator, invalidator, or engine can be centralized or its
functionality distributed. The module, manager, handler, detector,
interface, controller, normalizer, generator, invalidator, or
engine can include general or special purpose hardware, firmware,
or software embodied in a computer-readable (storage) medium for
execution by the processor. As used herein, a computer-readable
medium or computer-readable storage medium is intended to include
all mediums that are statutory (e.g., in the United States, under
35 U.S.C. 101), and to specifically exclude all mediums that are
non-statutory in nature to the extent that the exclusion is
necessary for a claim that includes the computer-readable (storage)
medium to be valid. Known statutory computer-readable mediums
include hardware (e.g., registers, random access memory (RAM),
non-volatile (NV) storage, to name a few), but may or may not be
limited to hardware.
[0327] In the example of a device (e.g., mobile device 350) making
an application or content request to an application server or
content provider 310, the request may be intercepted and routed to
the proxy server 325 which is coupled to the device 350 and the
application server/content provider 310. Specifically, the proxy
server is able to communicate with the local proxy (e.g., proxy 175
and 275 of the examples of FIG. 1 and FIG. 2 respectively) of the
mobile device 350, the local proxy forwards the data request to the
proxy server 325 in some instances for further processing and, if
needed, for transmission to the application server/content server
310 for a response to the data request.
[0328] In such a configuration, the host 300, or the proxy server
325 in the host server 300 can utilize intelligent information
provided by the local proxy in adjusting its communication with the
device in such a manner that optimizes use of network and device
resources. For example, the proxy server 325 can identify
characteristics of user activity on the device 350 to modify its
communication frequency. The characteristics of user activity can
be determined by, for example, the activity/behavior awareness
module 366 in the proxy controller 365 via information collected by
the local proxy on the device 350.
[0329] In one embodiment, communication frequency can be controlled
by the connection manager 395 of the proxy server 325, for example,
to adjust push frequency of content or updates to the device 350.
For instance, push frequency can be decreased by the connection
manager 395 when characteristics of the user activity indicate that
the user is inactive. In one embodiment, when the characteristics
of the user activity indicate that the user is subsequently active
after a period of inactivity, the connection manager 395 can adjust
the communication frequency with the device 350 to send data that
was buffered as a result of decreased communication frequency to
the device 350.
[0330] In addition, the proxy server 325 includes priority
awareness of various requests, transactions, sessions,
applications, and/or specific events. Such awareness can be
determined by the local proxy on the device 350 and provided to the
proxy server 325. The priority awareness module 367 of the proxy
server 325 can generally assess the priority (e.g., including
time-criticality, time-sensitivity, etc.) of various events or
applications; additionally, the priority awareness module 367 can
track priorities determined by local proxies of devices 350.
[0331] In one embodiment, through priority awareness, the
connection manager 395 can further modify communication frequency
(e.g., use or radio as controlled by the radio controller 396) of
the server 300 with the devices 350. For example, the server 300
can notify the device 350, thus requesting use of the radio if it
is not already in use when data or updates of an
importance/priority level which meets a criteria becomes available
to be sent.
[0332] In one embodiment, the proxy server 325 can detect multiple
occurrences of events (e.g., transactions, content, data received
from server/provider 310) and allow the events to accumulate for
batch transfer to device 350. Batch transfer can be cumulated and
transfer of events can be delayed based on priority awareness
and/or user activity/application behavior awareness as tracked by
modules 367 and/or 366. For example, batch transfer of multiple
events (of a lower priority) to the device 350 can be initiated by
the batching module 377 when an event of a higher priority (meeting
a threshold or criteria) is detected at the server 300. In
addition, batch transfer from the server 300 can be triggered when
the server receives data from the device 350, indicating that the
device radio is already in use and is thus on. In one embodiment,
the proxy server 325 can order the each messages/packets in a batch
for transmission based on event/transaction priority such that
higher priority content can be sent first in case connection is
lost or the battery dies, etc.
[0333] In one embodiment, the server 300 caches data (e.g., as
managed by the caching policy manager 355) such that communication
frequency over a network (e.g., cellular network) with the device
350 can be modified (e.g., decreased). The data can be cached, for
example, in the server cache 335 for subsequent retrieval or batch
sending to the device 350 to potentially decrease the need to turn
on the device 350 radio. The server cache 335 can be partially or
wholly internal to the host server 300, although in the example of
FIG. 3A it is shown as being external to the host 300. In some
instances, the server cache 335 may be the same as and/or
integrated in part or in whole with another cache managed by
another entity (e.g., the optional caching proxy server 199 shown
in the example of FIG. 1B), such as being managed by an application
server/content provider 310, a network service provider, or another
third party.
[0334] In one embodiment, content caching is performed locally on
the device 350 with the assistance of host server 300. For example,
proxy server 325 in the host server 300 can query the application
server/provider 310 with requests and monitor changes in responses.
When changed or new responses are detected (e.g., by the new data
detector 347), the proxy server 325 can notify the mobile device
350 such that the local proxy on the device 350 can make the
decision to invalidate (e.g., indicated as out-dated) the relevant
cache entries stored as any responses in its local cache.
Alternatively, the data invalidator module 368 can automatically
instruct the local proxy of the device 350 to invalidate certain
cached data, based on received responses from the application
server/provider 310. The cached data is marked as invalid, and can
get replaced or deleted when new content is received from the
content server 310.
[0335] Note that data change can be detected by the detector 347 in
one or more ways. For example, the server/provider 310 can notify
the host server 300 upon a change. The change can also be detected
at the host server 300 in response to a direct poll of the source
server/provider 310. In some instances, the proxy server 325 can in
addition, pre-load the local cache on the device 350 with the
new/updated data. This can be performed when the host server 300
detects that the radio on the mobile device is already in use, or
when the server 300 has additional content/data to be sent to the
device 350.
[0336] One or more the above mechanisms can be implemented
simultaneously or adjusted/configured based on application (e.g.,
different policies for different servers/providers 310). In some
instances, the source provider/server 310 may notify the host 300
for certain types of events (e.g., events meeting a priority
threshold level). In addition, the provider/server 310 may be
configured to notify the host 300 at specific time intervals,
regardless of event priority.
[0337] In one embodiment, the proxy server 325 of the host 300 can
monitor/track responses received for the data request from the
content source for changed results prior to returning the result to
the mobile device, such monitoring may be suitable when data
request to the content source has yielded same results to be
returned to the mobile device, thus preventing network/power
consumption from being used when no new changes are made to a
particular requested. The local proxy of the device 350 can
instruct the proxy server 325 to perform such monitoring or the
proxy server 325 can automatically initiate such a process upon
receiving a certain number of the same responses (e.g., or a number
of the same responses in a period of time) for a particular
request.
[0338] In one embodiment, the server 300, through the
activity/behavior awareness module 366, is able to identify or
detect user activity at a device that is separate from the mobile
device 350. For example, the module 366 may detect that a user's
message inbox (e.g., email or types of inbox) is being accessed.
This can indicate that the user is interacting with his/her
application using a device other than the mobile device 350 and may
not need frequent updates, if at all.
[0339] The server 300, in this instance, can thus decrease the
frequency with which new or updated content is sent to the mobile
device 350, or eliminate all communication for as long as the user
is detected to be using another device for access. Such frequency
decrease may be application specific (e.g., for the application
with which the user is interacting with on another device), or it
may be a general frequency decrease (E.g., since the user is
detected to be interacting with one server or one application via
another device, he/she could also use it to access other services.)
to the mobile device 350.
[0340] In one embodiment, the host server 300 is able to poll
content sources 310 on behalf of devices 350 to conserve power or
battery consumption on devices 350. For example, certain
applications on the mobile device 350 can poll its respective
server 310 in a predictable recurring fashion. Such recurrence or
other types of application behaviors can be tracked by the
activity/behavior module 366 in the proxy controller 365. The host
server 300 can thus poll content sources 310 for applications on
the mobile device 350 that would otherwise be performed by the
device 350 through a wireless (e.g., including cellular
connectivity). The host server can poll the sources 310 for new or
changed data by way of the HTTP access engine 345 to establish HTTP
connection or by way of radio controller 396 to connect to the
source 310 over the cellular network. When new or changed data is
detected, the new data detector 347 can notify the device 350 that
such data is available and/or provide the new/changed data to the
device 350.
[0341] In one embodiment, the connection manager 395 determines
that the mobile device 350 is unavailable (e.g., the radio is
turned off) and utilizes SMS to transmit content to the device 350,
for instance, via the SMSC shown in the example of FIG. 1B. SMS is
used to transmit invalidation messages, batches of invalidation
messages, or even content in the case where the content is small
enough to fit into just a few (usually one or two) SMS messages.
This avoids the need to access the radio channel to send overhead
information. The host server 300 can use SMS for certain
transactions or responses having a priority level above a threshold
or otherwise meeting a criteria. The server 300 can also utilize
SMS as an out-of-band trigger to maintain or wake-up an IP
connection as an alternative to maintaining an always-on IP
connection.
[0342] In one embodiment, the connection manager 395 in the proxy
server 325 (e.g., the heartbeat manager 398) can generate and/or
transmit heartbeat messages on behalf of connected devices 350 to
maintain a backend connection with a provider 310 for applications
running on devices 350.
[0343] For example, in the distributed proxy system, local cache on
the device 350 can prevent any or all heartbeat messages needed to
maintain TCP/IP connections required for applications from being
sent over the cellular, or other, network and instead rely on the
proxy server 325 on the host server 300 to generate and/or send the
heartbeat messages to maintain a connection with the backend (e.g.,
application server/provider 110 in the example of FIG. 1A). The
proxy server can generate the keep-alive (heartbeat) messages
independent of the operations of the local proxy on the mobile
device.
[0344] The repositories 312, 314, and/or 316 can additionally store
software, descriptive data, images, system information, drivers,
and/or any other data item utilized by other components of the host
server 300 and/or any other servers for operation. The repositories
may be managed by a database management system (DBMS), for example,
which may be but is not limited to Oracle, DB2, Microsoft Access,
Microsoft SQL Server, PostgreSQL, MySQL, FileMaker, etc.
[0345] The repositories can be implemented via object-oriented
technology and/or via text files and can be managed by a
distributed database management system, an object-oriented database
management system (OODBMS) (e.g., ConceptBase, FastDB Main Memory
Database Management System, JDOInstruments, ObjectDB, etc.), an
object-relational database management system (ORDBMS) (e.g.,
Informix, OpenLink Virtuoso, VMDS, etc.), a file system, and/or any
other convenient or known database management package.
[0346] FIG. 3B depicts a block diagram illustrating a further
example of components in the caching policy manager 355 in the
cache system shown in the example of FIG. 3A which is capable of
caching and adapting caching strategies for application (e.g.,
mobile application) behavior and/or network conditions.
[0347] The caching policy manager 355, in one embodiment, can
further include a metadata generator 303, a cache look-up engine
305, an application protocol module 356, a content source
monitoring engine 357 having a poll schedule manager 358, a
response analyzer 361, and/or an updated or new content detector
359. In one embodiment, the poll schedule manager 358 further
includes a host timing simulator 358a, a long poll request
detector/manager 358b, a schedule update engine 358c, and/or a time
adjustment engine 358d. The metadata generator 303 and/or the cache
look-up engine 305 can be coupled to the cache 335 (or, server
cache) for modification or addition to cache entries or querying
thereof.
[0348] In one embodiment, the proxy server (e.g., the proxy server
125 or 325 of the examples of FIG. 1B and FIG. 3A) can monitor a
content source for new or changed data via the monitoring engine
357. The proxy server, as shown, is an entity external to the
mobile device 250 of FIG. 2A-B. The content source (e.g.,
application server/content provider 110 of FIG. 1B) can be one that
has been identified to the proxy server (e.g., by the local proxy)
as having content that is being locally cached on a mobile device
(e.g., mobile device 150 or 250). The content source can be
monitored, for example, by the monitoring engine 357 at a frequency
that is based on polling frequency of the content source at the
mobile device. The poll schedule can be generated, for example, by
the local proxy and sent to the proxy server. The poll frequency
can be tracked and/or managed by the poll schedule manager 358.
[0349] For example, the proxy server can poll the host (e.g.,
content provider/application server) on behalf of the mobile device
and simulate the polling behavior of the client to the host via the
host timing simulator 358a. The polling behavior can be simulated
to include characteristics of a long poll request-response
sequences experienced in a persistent connection with the host
(e.g., by the long poll request detector/manager 358b). Note that
once a polling interval/behavior is set, the local proxy 275 on the
device-side and/or the proxy server 325 on the server-side can
verify whether application and application server/content host
behavior match or can be represented by this predicted pattern. In
general, the local proxy and/or the proxy server can detect
deviations and, when appropriate, re-evaluate and compute,
determine, or estimate another polling interval.
[0350] In one embodiment, the caching policy manager 355 on the
server-side of the distribute proxy can, in conjunction with or
independent of the proxy server 275 on the mobile device, identify
or detect long poll requests. For example, the caching policy
manager 355 can determine a threshold value to be used in
comparison with a response delay interval time (interval time `D`
shown in the example timing diagram of FIG. 17A-B) in a
request-response sequence for an application request to identify or
detect long poll requests, possible long poll requests (e.g.,
requests for a persistent connection with a host with which the
client communicates including, but not limited to, a long-held HTTP
request, a persistent connection enabling COMET style push, request
for HTTP streaming, etc.), or other requests which can otherwise be
treated as a long poll request.
[0351] For example, the threshold value can be determined by the
proxy 325 using response delay interval times for requests
generated by clients/applications across mobile devices which may
be serviced by multiple different cellular or wireless networks.
Since the proxy 325 resides on host 300 is able to communicate with
multiple mobile devices via multiple networks, the caching policy
manager 355 has access to application/client information at a
global level which can be used in setting threshold values to
categorize and detect long polls.
[0352] By tracking response delay interval times across
applications across devices over different or same networks, the
caching policy manager 355 can set one or more threshold values to
be used in comparison with response delay interval times for long
poll detection. Threshold values set by the proxy server 325 can be
static or dynamic, and can be associated with conditions and/or a
time-to-live (an expiration time/date in relative or absolute
terms).
[0353] In addition, the caching policy manager 355 of the proxy 325
can further determine the threshold value, in whole or in part,
based on network delays of a given wireless network, networks
serviced by a given carrier (service provider), or multiple
wireless networks. The proxy 325 can also determine the threshold
value for identification of long poll requests based on delays of
one or more application server/content provider (e.g., 110) to
which application (e.g., mobile application) or mobile client
requests are directed.
[0354] The proxy server can detect new or changed data at a
monitored content source and transmits a message to the mobile
device notifying it of such a change such that the mobile device
(or the local proxy on the mobile device) can take appropriate
action (e.g., to invalidate the cache elements in the local cache).
In some instances, the proxy server (e.g., the caching policy
manager 355) upon detecting new or changed data can also store the
new or changed data in its cache (e.g., the server cache 135 or 335
of the examples of FIG. 1B and FIG. 3A, respectively). The
new/updated data stored in the server cache 335 can be used in some
instances to satisfy content requests at the mobile device; for
example, it can be used after the proxy server has notified the
mobile device of the new/changed content and that the locally
cached content has been invalidated.
[0355] The metadata generator 303, similar to the metadata
generator 203 shown in the example of FIG. 2B, can generate
metadata for responses cached for requests at the mobile device
250. The metadata generator 303 can generate metadata for cache
entries stored in the server cache 335. Similarly, the cache
look-up engine 305 can include the same or similar functions are
those described for the cache look-up engine 205 shown in the
example of FIG. 2B.
[0356] The response analyzer 361 can perform any or all of the
functionalities related to analyzing responses received for
requests generated at the mobile device 250 in the same or similar
fashion to the response analyzer 246d of the local proxy shown in
the example of FIG. 2B. Since the proxy server 325 is able to
receive responses from the application server/content source 310
directed to the mobile device 250, the proxy server 325 (e.g., the
response analyzer 361) can perform similar response analysis steps
to determine cacheability, as described for the response analyzer
of the local proxy. Examples of response analysis procedures are
also described in conjunction with the flow charts shown in the
examples of FIG. 11-13. The responses can be analyzed in addition
to or in lieu of the analysis that can be performed at the local
proxy 275 on the mobile device 250.
[0357] Furthermore, the schedule update engine 358c can update the
polling interval of a given application server/content host based
on application request interval changes of the application at the
mobile device 250 as described for the schedule update engine in
the local proxy 275. The time adjustment engine 358d can set an
initial time at which polls of the application server/content host
is to begin to prevent the serving of out of date content once
again before serving fresh content as described for the schedule
update engine in the local proxy 275. Both the schedule updating
and the time adjustment algorithms can be performed in conjunction
with or in lieu of the similar processes performed at the local
proxy 275 on the mobile device 250.
[0358] FIG. 3C depicts a block diagram illustrating another example
of components in the caching policy manager 355 in the proxy server
375 on the server-side of the distributed proxy system shown in the
example of FIG. 3A which is capable of managing and detecting cache
defeating mechanisms and monitoring content sources.
[0359] The caching policy manager 355, in one embodiment, can
further include a cache defeating source manager 352, a content
source monitoring engine 357 having a poll schedule manager 358,
and/or an updated or new content detector 359. The cache defeating
source manager 352 can further include an identifier modifier
module 353 and/or an identifier pattern tracking module 354.
[0360] In one embodiment, the proxy server (e.g., the proxy server
125 or 325 of the examples of FIG. 1B and FIG. 3A) can monitor a
content source for new or changed data via the monitoring engine
357. The content source (e.g., application server/content provider
110 of FIG. 1B or 310 of FIG. 3A) can be one that has been
identified to the proxy server (e.g., by the local proxy) as having
content that is being locally cached on a mobile device (e.g.,
mobile device 150 or 250). The content source 310 can be monitored,
for example, by the monitoring engine 357 at a frequency that is
based on polling frequency of the content source at the mobile
device. The poll schedule can be generated, for example, by the
local proxy and sent to the proxy server 325. The poll frequency
can be tracked and/or managed by the poll schedule manager 358.
[0361] In one embodiment, the proxy server 325 uses a normalized
identifier or modified identifier in polling the content source 310
to detect new or changed data (responses). The normalized
identifier or modified identifier can also be used by the proxy
server 325 in storing responses on the server cache 335. In
general, the normalized or modified identifiers can be used when
cache defeat mechanisms are employed for cacheable content. Cache
defeat mechanisms can be in the form of a changing parameter in an
identifier such as a URI or URL and can include a changing
time/data parameter, a randomly varying parameter, or other types
parameters.
[0362] The normalized identifier or modified identifier removes or
otherwise replaces the changing parameter for association with
subsequent requests and identification of associated responses and
can also be used to poll the content source. In one embodiment, the
modified identifier is generated by the cache defeating source
manager 352 (e.g., the identifier modifier module 353) of the
caching policy manager 355 on the proxy server 325 (server-side
component of the distributed proxy system). The modified identifier
can utilize a substitute parameter (which is generally static over
a period of time) in place of the changing parameter that is used
to defeat cache.
[0363] The cache defeating source manager 352 optionally includes
the identifier pattern tracking module 354 to track, store, and
monitor the various modifications of an identifier or identifiers
that address content for one or more content sources (e.g.,
application server/content host 110 or 310) to continuously verify
that the modified identifiers and/or normalized identifiers used by
the proxy server 325 to poll the content sources work as predicted
or intended (e.g., receive the same responses or responses that are
otherwise still relevant compared to the original, unmodified
identifier).
[0364] In the event that the pattern tracking module 354 detects a
modification or normalization of an identifier that causes erratic
or unpredictable behavior (e.g., unexpected responses to be sent)
on the content source, the tracking module 354 can log the
modification and instruct the cache defeating source manager 352 to
generate another modification/normalization, or notify the local
proxy (e.g., local proxy 275) to generate another
modification/normalization for use in polling the content source.
In the alternative or in parallel, the requests from the given
mobile application/client on the mobile device (e.g., mobile device
250) can temporarily be sent across the network to the content
source for direct responses to be provided to the mobile device
and/or until a modification of an identifier which works can be
generated.
[0365] In one embodiment, responses are stored as server cache
elements in the server cache when new or changed data is detected
for a response that is already stored on a local cache (e.g., cache
285) of the mobile device (e.g., mobile device 250). Therefore, the
mobile device or local proxy 275 can connect to the proxy server
325 to retrieve the new or changed data for a response to a request
which was previously cached locally in the local cache 285 (now
invalid, out-dated, or otherwise determined to be irrelevant).
[0366] The proxy server 325 can detect new or changed data at a
monitored application server/content host 310 and transmits a
message to the mobile device notifying it of such a change such
that the mobile device (or the local proxy on the mobile device)
can take appropriate action (e.g., to invalidate the cache elements
in the local cache). In some instances, the proxy server (e.g., the
caching policy manager 355), upon detecting new or changed data,
can also store the new or changed data in its cache (e.g., the
server cache 135 or 335 of the examples of FIG. 1B and FIG. 3A,
respectively). The updated/new data stored in the server cache can
be used, in some instances, to satisfy content requests at the
mobile device; for example, it can be used after the proxy server
has notified the mobile device of the new/changed content and that
the locally cached content has been invalidated.
[0367] FIG. 3D depicts a block diagram illustrating examples of
additional components in proxy server 325 shown in the example of
FIG. 3A which is further capable of performing mobile traffic
categorization and policy implementation based on application
behavior and/or traffic priority.
[0368] In one embodiment of the proxy server 325, the traffic
shaping engine 375 is further coupled to a traffic analyzer 336 for
categorizing mobile traffic for policy definition and
implementation for mobile traffic and transactions directed to one
or more mobile devices (e.g., mobile device 250 of FIG. 2A-2D) or
to an application server/content host (e.g., 110 of FIG. 1A-1B). In
general, the proxy server 325 is remote from the mobile devices and
remote from the host server, as shown in the examples of FIG.
1A-1B. The proxy server 325 or the host server 300 can monitor the
traffic for multiple mobile devices and is capable of categorizing
traffic and devising traffic policies for different mobile
devices.
[0369] In addition, the proxy server 325 or host server 300 can
operate with multiple carriers or network operators and can
implement carrier-specific policies relating to categorization of
traffic and implementation of traffic policies for the various
categories. For example, the traffic analyzer 336 of the proxy
server 325 or host server 300 can include one or more of, a
prioritization engine 341a, a time criticality detection engine
341b, an application state categorizer 341c, and/or an application
traffic categorizer 341d.
[0370] Each of these engines or modules can track different
criterion for what is considered priority, time critical,
background/foreground, or interactive/maintenance based on
different wireless carriers. Different criterion may also exist for
different mobile device types (e.g., device model, manufacturer,
operating system, etc.). In some instances, the user of the mobile
devices can adjust the settings or criterion regarding traffic
category and the proxy server 325 is able to track and implement
these user adjusted/configured settings.
[0371] In one embodiment, the traffic analyzer 336 is able to
detect, determined, identify, or infer, the activity state of an
application on one or more mobile devices (e.g., mobile device 150
or 250) which traffic has originated from or is directed to, for
example, via the application state categorizer 341c and/or the
traffic categorizer 341d. The activity state can be determined
based on whether the application is in a foreground or background
state on one or more of the mobile devices (via the application
state categorizer 341c) since the traffic for a foreground
application vs. a background application may be handled differently
to optimize network use.
[0372] In the alternate or in combination, the activity state of an
application can be determined by the wirelessly connected mobile
devices (e.g, via the application behavior detectors in the local
proxies) and communicated to the proxy server 325. For eample, the
activity state can be determined, detected, identified, or inferred
with a level of certainty of heuristics, based on the backlight
status at mobile devices (e.g., by a backlight detector) or other
software agents or hardware sensors on the mobile device, including
but not limited to, resistive sensors, capacitive sensors, ambient
light sensors, motion sensors, touch sensors, etc. In general, if
the backlight is on, the traffic can be treated as being or
determined to be generated from an application that is active or in
the foreground, or the traffic is interactive. In addition, if the
backlight is on, the traffic can be treated as being or determined
to be traffic from user interaction or user activity, or traffic
containing data that the user is expecting within some time
frame.
[0373] The activity state can be determined from assessing,
determining, evaluating, inferring, identifying user activity at
the mobile device 250 (e.g., via the user activity module 215) and
communicated to the proxy server 325. In one embodiment, the
activity state is determined based on whether the traffic is
interactive traffic or maintenance traffic. Interactive traffic can
include transactions from responses and requests generated directly
from user activity/interaction with an application and can include
content or data that a user is waiting or expecting to receive.
Maintenance traffic may be used to support the functionality of an
application which is not directly detected by a user. Maintenance
traffic can also include actions or transactions that may take
place in response to a user action, but the user is not actively
waiting for or expecting a response.
[0374] The time criticality detection engine 341b can generally
determine, identify, infer the time sensitivity of data contained
in traffic sent from the mobile device 250 or to the mobile device
from the host server 300 or proxy server 325, or the application
server (e.g., app server/content source 110). For example, time
sensitive data can include, status updates, stock information
updates, IM presence information, email messages or other messages,
actions generated from mobile gaming applications, webpage
requests, location updates, etc.
[0375] Data that is not time sensitive or time critical, by nature
of the content or request, can include requests to delete messages,
mark-as-read or edited actions, application-specific actions such
as a add-friend or delete-friend request, certain types of
messages, or other information which does not frequently changing
by nature, etc. In some instances when the data is not time
critical, the timing with which to allow the traffic to be sent to
a mobile device is based on when there is additional data that
needs to the sent to the same mobile device. For example, traffic
shaping engine 375 can align the traffic with one or more
subsequent transactions to be sent together in a single power-on
event of the mobile device radio (e.g, using the alignment module
378 and/or the batching module 377). The alignment module 378 can
also align polling requests occurring close in time directed to the
same host server, since these request are likely to be responded to
with the same data.
[0376] In general, whether new or changed data is sent from a host
server to a mobile device can be determined based on whether an
application on the mobile device to which the new or changed data
is relevant, is running in a foreground (e.g., by the application
state categorizer 341c), or the priority or time criticality of the
new or changed data. The proxy server 325 can send the new or
changed data to the mobile device if the application is in the
foreground on the mobile device, or if the application is in the
foreground and in an active state interacting with a user on the
mobile device, and/or whether a user is waiting for a response that
would be provided in the new or changed data. The proxy server 325
(or traffic shaping engine 375) can send the new or changed data
that is of a high priority or is time critical.
[0377] Similarly, the proxy server 325 (or the traffic shaping
engine 375) can suppressing the sending of the new or changed data
if the application is in the background on the mobile device. The
proxy server 325 can also suppress the sending of the new or
changed data if the user is not waiting for the response provided
in the new or changed data; wherein the suppressing is performed by
a proxy server coupled to the host server and able to wirelessly
connect to the mobile device.
[0378] In general, if data, including new or change data is of a
low priority or is not time critical, the proxy server can waiting
to transfer the data until after a time period, or until there is
additional data to be sent (e.g. via the alignment module 378
and/or the batching module 377).
[0379] FIG. 3E depicts a block diagram illustrating examples of
additional components in the traffic shaping engine 375 of the
example of FIG. 3A which is further capable of aligning data
transfer to a mobile or broadband device, or other recipient, to
optimize connections established for transmission in a wireless
network or broadband network.
[0380] In one embodiment of the proxy server 325, the traffic
shaping engine 375 further includes a notification engine 379 and
the alignment module 378 includes an adjusted poll tracker 378a and
the batching module 377 further includes a connection trigger
377a.
[0381] In one embodiment, the proxy server 325 is able to poll
distinct hosts servicing various applications (e.g., first and
second services) on a given mobile device at a schedule. The
polling schedule can be set by the local proxy (e.g., proxy 275 of
FIG. 2A-2E) and can include assigned polling intervals for
applications on a mobile device (e.g., device 250) which may have
been adjusted. The polling schedules can be tracked by the adjusted
poll tracker 378a in the alignment module 378 of the traffic
shaping engine 375 in the proxy server 325, for example. The
adjusted polling intervals of one service/one application can be
determined based on the polling interval of another service on the
mobile device, such that data received at the remote proxy 325 can
be provided to the mobile device in batch, for example, by the
batching module 377.
[0382] The polling schedule can also include an initial start time
(t0) to start polling on behalf of multiple applications on a given
mobile device. The initial start time (e.g., a mutual starting
point in time) of a first poll of the distinct hosts servicing the
first and second services can be selected, for example, by the
local proxy 275 (e.g., proxy 275 of FIG. 2A-2E), and in some
instances, by the proxy server 325. When determined by the local
proxy, the local proxy communicates the mutual starting point in
time for polls to the proxy server 325. In one embodiment, the
mutual starting point in time is set to be in the future to
compensate for communication delay.
[0383] In one embodiment, if a given mobile client/mobile
application is not on or active, or if a given mobile device 250 is
not connected to the wireless network, the connection trigger 377a
can send a trigger (e.g., out of band) trigger to the mobile device
or the local proxy on the mobile device to request that the radio
be powered and/or to activate one or more relevant applications.
For example, the batching module 377 may have batched various
content or data to be sent for multiple applications on a given
mobile device and if the mobile clients/applications are not on or
active, the connection trigger 377a can send a trigger requesting
the application to activate. Alternatively, the notification engine
379 can send the mobile device 250 an indication that there is data
ready to be sent, requesting the mobile device 250 to power on the
radio if currently in off-mode.
[0384] Note that the proxy server 325 monitors multiple mobile
devices and tracks application characteristics and user
behavior/characteristics across multiple devices, users, and
networks. Thus, the above described features pertaining to adjusted
poll interval trackers, although drawn to an example directed to
multiple applications on a given device, note that the same is
tracked for multiple devices, having installed thereon its own
other set of applications, for which adjusted poll intervals or
polling schedules are computed based on applications on each mobile
device by, for example the local proxy residing there on (e.g., the
components illustrated in FIG. 2E of a local proxy 275 which may be
installed on one or more of the multiple mobile devices serviced by
the proxy server 325).
[0385] Note that since the proxy server 325 manages the traffic
to/from multiple mobile devices, in one network, across networks,
in one geographical locale, across multiple geographical locales,
for one network operator, or across multiple network operators, the
proxy server 325 can align traffic and batch transfer of data based
on overview or aggregate data of traffic conditions or network
conditions. The proxy server 325 can prioritize data transfer to
mobile devices, for example, when network congestion is detected.
For example, the proxy server 325 can transfer data to mobile
devices where the type or level of subscription of the device user,
tiered or staggered based on highest priority of content to be
transferred to be the mobile devices (e.g., a batch of data may be
transferred first to mobile device A, compared to mobile device B,
when the highest priority data for device A is of higher priority
than device B).
[0386] Note that there may be one proxy server 325 for a
geographical locale, or for a specific network operator, for a type
of web service, or any combination of the above, for example. Based
on the different servicing entities, the proxy server 325 can
aggregate different types of information pertaining to network
traffic, operator settings, application preferences/requirements,
user preferences, subscription-related parameters, various
combination of the above can be used by the proxy 325 in optimizing
connections need to be established by receiving mobile devices.
Multiple proxy servers 325 servicing different networks in a
geographical locale, different operators can share traffic,
subscription, user, or application level information there between,
to further facilitate network resource utilization, traffic
management, and in some instances to facilitate alignment of data
transfer to mobile devices.
[0387] FIG. 4 depicts another flow diagram illustrating an example
process for distributed content caching between a mobile device and
a proxy server and the distributed management of content caching.
As shown herein, the disclosed technology is a distributed caching
model with various aspects of caching tasks split between the
client-side/mobile device side (e.g., local proxy 275 in the
example of FIG. 2) and the server side (e.g., proxy server 325 of
FIG. 3).
[0388] In general the device-side responsibilities can include
deciding whether a response to a particular request can be and/or
should be cached. The device-side of the proxy can make this
decision based on information (e.g., timing characteristics,
detected pattern, detected pattern with heuristics, indication of
predictability or repeatability) collected from/during both request
and response and cache it (e.g., storing it in a local cache on the
mobile device). The device side can also notify the server-side in
the distributed cache system of the local cache event and notify it
monitor the content source (e.g., application server/content
provider 110 of FIG. 1B-C).
[0389] The device side can further instruct the server side of the
distributed proxy to periodically validate the cache response
(e.g., by way of polling, or sending polling requests to the
content source). The device side can further decide whether a
response to a particular cache request should be returned from the
local cache (e.g., whether a cache hit is detected). The decision
can be made by the device side (e.g., the local proxy on the
device) using information collected from/during request and/or
responses received from the content source.
[0390] In general, the server-side responsibilities can include
validating cached responses for relevancy (e.g., determine whether
a cached response is still valid or relevant to its associated
request). The server-side can send the mobile device an
invalidation request to notify the device side when a cached
response is detected to be no longer valid or no longer relevant
(e.g., the server invalidates a given content source). The device
side then can remove the response from the local cache.
[0391] The diagram of FIG. 4 illustrates caching logic processes
performed for each detected or intercepted request (e.g., HTTP
request) detected at a mobile device (e.g., client-side of the
distributed proxy). In step 602, the client-side of the proxy
(e.g., local proxy 275) receives a request (from an application
(e.g., mobile application) or mobile client). In step 604, URL is
normalized and in step 606 the client-side checks to determine if
the request is cacheable. If the request is determined to be not
cacheable in step 612, the request is sent to the source
(application server/content provider) in step 608 and the response
is received 610 and delivered to the requesting application 622,
similar to a request-response sequence without interception by the
client side proxy.
[0392] If the request is determined to be cacheable, in step 612,
the client-side looks up the cache to determine whether a cache
entry exists for the current request. If so, in step 624, the
client-side can determine whether the entry is valid and if so, the
client side can check the request to see if includes a validator
(e.g., a modified header or an entity tag) in step 615. For
example, the concept of validation is eluded to in section 13.3 of
RFC 2616 which describes in possible types of headers (e.g., eTAG,
Modified_Since, must_revlaidate, pragma no_cache) and forms a
validating response 632 if so to be delivered to the requesting
application in step 622. If the request does not include a
validator as determined by step 615, a response is formed from the
local cache in step 630 and delivered to the requesting application
in step 622. This validation step can be used for content that
would otherwise normally be considered un-cacheable.
[0393] If, instead, in step 624, the cache entry is found but
determined to be no longer valid or invalid, the client side of the
proxy sends the request 616 to the content source (application
server/content host) and receives a response directly from the
source in step 618. Similarly, if in step 612, a cache entry was
not found during the look up, the request is also sent in step 616.
Once the response is received, the client side checks the response
to determine if it is cacheable in step 626. If so, the response is
cached in step 620. The client then sends another poll in step 614
and then delivers the response to the requesting application in
step 622.
[0394] FIG. 5 depicts a sequence diagram showing how data requests
from a mobile device 450 to an application server/content provider
495 in a wireless network can be coordinated by a distributed proxy
system 460 in a manner such that network and battery resources are
conserved through using content caching and monitoring performed by
the distributed proxy system 460.
[0395] In satisfying application or client requests on a mobile
device 450 without the distributed proxy system 460, the mobile
device 450, or the software widget executing on the device 450,
performs a data request 452 (e.g., an HTTP GET, POST, or other
request) directly to the application server 495 and receives a
response 404 directly from the server/provider 495. If the data has
been updated, the widget 455 on the mobile device 450 can refreshes
itself to reflect the update and waits for small period of time and
initiates another data request to the server/provider 495.
[0396] In one embodiment, the requesting client or software widget
455 on the device 450 can utilize the distributed proxy system 460
in handling the data request made to server/provider 495. In
general, the distributed proxy system 460 can include a local proxy
465 (which is typically considered a client-side component of the
system 460 and can reside on the mobile device 450), a caching
proxy 475 (considered a server-side component 470 of the system 460
and can reside on the host server 485 or be wholly or partially
external to the host server 485), and a host server 485. The local
proxy 465 can be connected to the caching proxy 475 and host server
485 via any network or combination of networks.
[0397] When the distributed proxy system 460 is used for
data/application requests, the widget 455 can perform the data
request 456 via the local proxy 465. The local proxy 465, can
intercept the requests made by device applications, and can
identify the connection type of the request (e.g., an HTTP get
request or other types of requests). The local proxy 465 can then
query the local cache for any previous information about the
request (e.g., to determine whether a locally stored response is
available and/or still valid). If a locally stored response is not
available or if there is an invalid response stored, the local
proxy 465 can update or store information about the request, the
time it was made, and any additional data, in the local cache. The
information can be updated for use in potentially satisfying
subsequent requests.
[0398] The local proxy 465 can then send the request to the host
server 485 and the host server 485 can perform the request 456 and
returns the results in response 458. The local proxy 465 can store
the result and, in addition, information about the result and
returns the result to the requesting widget 455.
[0399] In one embodiment, if the same request has occurred multiple
times (within a certain time period) and it has often yielded same
results, the local proxy 465 can notify 460 the server 485 that the
request should be monitored (e.g., steps 462 and 464) for result
changes prior to returning a result to the local proxy 465 or
requesting widget 455.
[0400] In one embodiment, if a request is marked for monitoring,
the local proxy 465 can now store the results into the local cache.
Now, when the data request 466, for which a locally response is
available, is made by the widget 455 and intercepted at the local
proxy 465, the local proxy 465 can return the response 468 from the
local cache without needing to establish a connection communication
over the wireless network.
[0401] In addition, the server proxy performs the requests marked
for monitoring 470 to determine whether the response 472 for the
given request has changed. In general, the host server 485 can
perform this monitoring independently of the widget 455 or local
proxy 465 operations. Whenever an unexpected response 472 is
received for a request, the server 485 can notify the local proxy
465 that the response has changed (e.g., the invalidate
notification in step 474) and that the locally stored response on
the client should be erased or replaced with a new response.
[0402] In this case, a subsequent data request 476 by the widget
455 from the device 450 results in the data being returned from
host server 485 (e.g., via the caching proxy 475), and in step 478,
the request is satisfied from the caching proxy 475. Thus, through
utilizing the distributed proxy system 460, the wireless (cellular)
network is intelligently used when the content/data for the widget
or software application 455 on the mobile device 450 has actually
changed. As such, the traffic needed to check for the changes to
application data is not performed over the wireless (cellular)
network. This reduces the amount of generated network traffic and
shortens the total time and the number of times the radio module is
powered up on the mobile device 450, thus reducing battery
consumption and, in addition, frees up network bandwidth.
[0403] FIG. 6 depicts a table 700 showing examples of different
traffic or application category types which can be used in
implementing network access and content delivery policies. For
example, traffic/application categories can include interactive or
background, whether a user is waiting for the response,
foreground/background application, and whether the backlight is on
or off.
[0404] FIG. 7 depicts a table 800 showing examples of different
content category types which can be used in implementing network
access and content delivery policies. For example, content category
types can include content of high or low priority, and time
critical or non-time critical content/data.
[0405] FIG. 8 depicts an interaction diagram showing how
application (e.g., mobile application) 955 polls having data
requests from a mobile device to an application server/content
provider 995 over a wireless network can be can be cached on the
local proxy 965 and managed by the distributed caching system
(including local proxy 965 and the host server 985 (having server
cache 935 or caching proxy server 975)).
[0406] In one example, when the mobile application/widget 955 polls
an application server/provider 932, the poll can locally be
intercepted 934 on the mobile device by local proxy 965. The local
proxy 965 can detect that the cached content is available for the
polled content in the request and can thus retrieve a response from
the local cache to satisfy the intercepted poll 936 without
requiring use of wireless network bandwidth or other wireless
network resources. The mobile application/widget 955 can
subsequently receive a response to the poll from a cache entry
938.
[0407] In another example, the mobile application widget 955 polls
the application server/provider 940. The poll is intercepted 942 by
the local proxy 965 and detects that cache content is unavailable
in the local cache and decides to set up the polled source for
caching 944. To satisfy the request, the poll is forwarded to the
content source 946. The application server/provider 995 receives
the poll request from the application and provides a response to
satisfy the current request 948. In 950, the application (e.g.,
mobile application)/widget 955 receives the response from the
application server/provider to satisfy the request.
[0408] In conjunction, in order to set up content caching, the
local proxy 965 tracks the polling frequency of the application and
can set up a polling schedule to be sent to the host server 952.
The local proxy sends the cache set up to the host server 954. The
host server 985 can use the cache set up which includes, for
example, an identification of the application server/provider to be
polled and optionally a polling schedule 956. The host server 985
can now poll the application server/provider 995 to monitor
responses to the request 958 on behalf of the mobile device. The
application server receives the poll from the host server and
responds 960. The host server 985 determines that the same response
has been received and polls the application server 995 according to
the specified polling schedule 962. The application server/content
provider 995 receives the poll and responds accordingly 964.
[0409] The host server 985 detects changed or new responses and
notifies the local proxy 965. The host server 985 can additional
store the changed or new response in the server cache or caching
proxy 968. The local proxy 965 receives notification from the host
server 985 that new or changed data is now available and can
invalidate the affected cache entries 970. The next time the
application (e.g., mobile application)/widget 955 generates the
same request for the same server/content provider 972, the local
proxy determines that no valid cache entry is available and instead
retrieves a response from the server cache 974, for example,
through an HTTP connection. The host server 985 receives the
request for the new response and sends the response back 976 to the
local proxy 965. The request is thus satisfied from the server
cache or caching proxy 978 without the need for the mobile device
to utilize its radio or to consume mobile network bandwidth thus
conserving network resources.
[0410] Alternatively, when the application (e.g., mobile
application) generates the same request in step 980, the local
proxy 965, in response to determining that no valid cache entry is
available, forwards the poll to the application server/provider in
step 982 over the mobile network. The application server/provider
995 receives the poll and sends the response back to the mobile
device in step 984 over the mobile network. The request is thus
satisfied from the server/provider using the mobile network in step
986.
Example Signaling or Connection Modeling
[0411] FIG. 9 depicts a flow diagram illustrating an example
process for modeling signaling of a mobile device (e.g., any
wireless device) in a mobile network. The operations or steps
illustrated with respect to FIG. 9 are discussed with performance
by a mobile device. However, the operations or steps may be
performed in various embodiments by any of the one or more
components of the Open Channel architecture discussed herein. For
example, the operations or steps may be performed by an OC client
proxy of a mobile device (e.g., OC client proxy 175 of mobile
device 150 of FIG. 1A-1), a mobile device (e.g., mobile device
150), an OC (host) server (e.g., OC (host) server 100), one or more
processors, and/or other components, modules, engines, or tools
discussed herein. Additional or fewer data flow operations are
possible.
[0412] To begin, at step 1010, the mobile device tracks
transactions initiated by mobile applications executing on the
mobile device in the mobile network. At step 1012, the mobile
device determines if the transactions cause network signaling
requiring a corresponding radio connection. At step 1014, the
mobile device models the network signaling for the mobile
device.
[0413] FIG. 10 depicts a flow diagram illustrating an example
process for modeling signaling of a mobile device (e.g., any
wireless device) in a mobile network. The operations or steps
illustrated with respect to FIG. 9 are discussed with performance
by a mobile device. However, the operations or steps may be
performed in various embodiments by one or more components of the
Open Channel architecture discussed herein. For example, the
operations or steps may be performed by an OC client proxy of a
mobile device (e.g., OC client proxy 175 of mobile device 150 of
FIG. 1A-1), a mobile device (e.g., mobile device 150), an OC (host)
server (e.g., OC (host) server 100), one or more processors, and/or
other components, modules, engines, or tools discussed herein.
Additional or fewer data flow operations are possible.
[0414] To begin, at step 1020, the mobile device accesses a radio
log associated with the mobile device. The radio log can indicate a
state of a mobile device radio. At step 1022, the mobile device
access a traffic activity log associated with the mobile device.
The traffic activity log can indicate various traffic metrics
measured at multiple measurement points in the mobile device. At
step 1024, the mobile device calculates one or more fields based on
one or more of the radio log and the traffic activity log. At step
1026, the mobile device models the network signaling for the mobile
device based on the one or more fields.
Example General Connection and Time Calculations
[0415] FIG. 11A-FIG. 16D depict example field calculations for use
in determining general connection and time calculations. As
discussed herein, the various field calculations can be used to
model the signaling in a mobile network. Importantly, the example
field calculations discussed below include the following notations:
[0416] Short time stamp form (e.g., 07:26:00.000 is used instead of
full form 2012-10-30 07:26:00.000); [0417] Only required fields for
calculations are shown in input logs; [0418] An example default
value for network delay is used (e.g., 15 000 milliseconds); [0419]
An example default value for request delay is used (e.g., 1 000
milliseconds); [0420] An example default value for split ratio is
used (e.g., 3000); [0421] The terms "dormancy" and "network delay"
are used synonymously.
[0422] The example connections and time calculations discussed
herein are primarily based on two major data collections: radio up
intervals and filtered netLogs (also referred to as traffic
activity logs).
[0423] As discussed above, the expanded fields can be divided into
multiple types. For example, the expanded fields can include a
connection flag type and a time connected counts type.
Additionally, the expanded fields can be divided into several
categories as illustrated above in Table 1.
[0424] More specifically, FIGS. 11A and 11B illustrate calculation
of example real (or actual) radio time intervals and corresponding
fields. FIGS. 12A and 12B illustrate calculation of example virtual
radio time intervals and corresponding fields. FIGS. 13A and 13B
illustrate calculation of example simulated radio time intervals
and corresponding fields. FIGS. 14A and 14B illustrate calculation
of example simulated virtual radio time intervals and corresponding
fields. FIGS. 15A-15D illustrate calculation of simulated per
application radio up intervals. FIGS. 16A-16D illustrate
calculation of virtual simulated per application radio up intervals
and corresponding fields.
Example Real (or Actual) Fields Calculations
[0425] Referring first to FIGS. 11A and 11B which illustrate an
example operation for calculation of a real (or actual) radio up
interval and graphical illustration of an example real (or actual)
radio time interval, respectively. The real (or actual) fields
calculation includes calculation of an actual connection field and
an actual time connected field.
[0426] The actual connection field indicates a real connection that
occurs over the network. The radio log can indicate various states
of a mobile device radio over a period of time and thus can be used
to make the actual connection field calculation. That is, the state
of the mobile device radio can be used to determine if the mobile
device radio is/was up. For example, in some embodiments, if the
current state of radio log indicates that the current state of the
mobile device radio is set to a DATA_ACTIVITY_CONNECTED state or a
WCDMA_DCH state then the mobile device radio is considered to be up
(or active). Conversely, if the current state of the mobile device
radio is set to a DATA_ACTIVITY_DORMANT state or an IDLE state then
the mobile device radio is considered to be down (or inactive).
[0427] In one embodiment, an actual time field is calculated
indicating a total time interval during which the radio channel was
up for a mobile device. That is, the actual time field indicates
the time during which the network channel was used to transfer data
(e.g., to or from client). The actual time can be calculated as the
sum of all time intervals between two nearest net log items when
the net log items are in the radio up interval. Importantly, when
calculating the actual time field, if a particular net log item is
the first net log item in the log after a radio up log item, then
its actual time of connection equals to the sum if two values:
[0428] time interval between this net log item and the nearest net
log after it [0429] time interval between radio up and this net log
item
[0430] As discussed with reference to the example of FIG. 11B, the
actual connection fields and the actual time fields can be
calculated by first reading a radio access log and a traffic
activity log (also referred to herein as a net log or network log)
associated with a mobile device. Together the relevant portions of
the radio access log and the traffic activity log can be referred
to herein as an input log associated with a mobile device. In the
example of FIG. 11A, table 3 below, indicates the relevant portions
of the input net log and input radio log (collectively, input
log).
TABLE-US-00003 TABLE 3 Input Net log and Radio fields RL1
07:26:00.000 data_activity_connected data_activity_dormant Radio up
.uparw. NL1 07:26:00.500 32 234 23 42 0 0 mobile_gprs NL2
07:26:20.000 43 23 342 424 0 0 mobile_gprs NL3 07:27:00.000 32 234
423 234 0 0 mobile_gprs RL2 07:30:00.000 data_activity_dormant
data_activity_connected Radio down .dwnarw.
[0431] As indicated above, the input net log and input radio log
each include various net log items. The net log items are indicated
by the connotation "NLx" while the radio log items are indicated
using the "RLx" connotation.
[0432] The analysis core tool such as, for example, analysis core
255a of FIG. 2E or CRSC analysis core 375a of FIG. 3E process the
input log(s) to, for example, calculate one or more additional
fields based on the one or more input logs (e.g., radio log and the
traffic activity log). This process can include utilizing one or
more long poll techniques to split one net log item into two or
more net log items. Use of the one of more long poll techniques is
illustrated and discussed in greater detail with reference to FIGS.
19A and 19B. As shown in this example, the analysis core tool
calculates an actual connection field (or flag) and actual time
field for each net log item. An example output table 4 is
illustrated below.
TABLE-US-00004 TABLE 4 Output Net log fields TimeStamp Actual
connection Actual Time NL1 07:26:00.500 1 20 000 NL2 07:26:20.000 0
40 000 NL3 07:27:00.000 0 180 000 TOTAL 1 240 000
[0433] In this example, RL1 is radio up log because its "state"
field is data_activity_connected and "prev_state" is
data_activity_dormant. Similarly, RL2 is radio down log because its
"state" field is data_activity_dormant and "prev_state" is
data_activity_connected. Accordingly, the actual radio up interval
is: 07:30:00.000-07:26:00.000=4 min=240 sec=240 000 ms.
[0434] With respect to the actual connection calculation, NL1 makes
an actual connection because it is first net log after the radio up
so this net log starts a new connection. NL2 and NL3 occurred when
radio was already risen up, so they don't start a new connection.
Therefore, actual connection NL1=1; actual connection NL2=0; and
actual connection NL3=0. With respect to the actual time
calculation: [0435] actual time NL1=[RL1, NL1]+[NL1, NL2]; [0436]
actual time NL2=[NL2, NL3]; and [0437] actual time NL3=[NL3, RL2].
where, [0438] [RL1, NL1] is time interval between radio log item
RL1 and net log item NL1; [0439] [NL1, NL2] is the same for net log
item NL1 and net log item NL2; [0440] [NL2, NL3] is the same for
NL2 and NL3; [0441] [NL3, RL2] is time interval between net log
item NL3 and radio log item RL2;
Also,
[0441] [0442] [RL1, NL1]=07:26:00.500-07:26:00.000=0 500 [0443]
[NL1, NL2]=07:26:20.000-07:26:00.500=19 500 [0444] [NL2,
NL3]=07:27:00.000-07:26:20.000=20 000 [0445] [NL3,
RL2]=07:30:00.000-07:27:00.000=180 000
Thus,
[0445] [0446] actual time
NL1=[07:26:00.500-07:26:00.000]+[07:26:20.000-07:26:00.500]=500+19
500=20 000; [0447] actual time NL2=07:27:00.000-07:26:20.000=40
000; [0448] actual time NL3=07:30:00.000-07:27:00.000=180 000;
Example Virtual Fields Calculations
[0449] Referring next to FIG. 12A and FIG. 12B which illustrate an
example operation for calculation of a virtual radio up interval
and graphical illustration of an example virtual radio up interval,
respectively. More specifically, the virtual fields calculation
includes calculation of a virtual connection field and a virtual
time connected field.
[0450] As discussed above, a analysis core tool or module (not
shown) can calculate expanded fields that are maintained and
utilized by the analysis core tool to model signaling of a mobile
device in a mobile network. More specifically, the analysis core
tool can model the effects of the Open Channel architecture (e.g.,
the distributed caching techniques including the Signal
Optimization and Extended Caching techniques discussed herein). For
example, the analysis core tool or module such as, for example,
analysis core 255a of FIG. 2E or CRSC analysis core 375a of FIG.
3E, can calculate the virtual radio up intervals. The calculation
can include calculating one or more additional fields based on one
or more input logs (e.g., radio log and a traffic activity log
including cache hit information).
[0451] More specifically, as shown in the example of FIG. 12B, the
analysis core tool or module utilizes the radio Logs and the
cacheHit netLogs to calculate the virtual radio up intervals. The
virtual fields illustrate which connections would happen `but for`
the Open Channel client on mobile device. FIG. 12A, illustrates an
example architecture for calculation of virtual fields.
[0452] The virtual connection fields indicate a virtual connection
that is made either through cache (no radio up) or through a real
(actual) connection. That is, the virtual connections illustrate
what connections would occur if no Open Channel client was
operating on the mobile device. Similarly, the virtual time field
indicates a time interval during which the radio channel would be
up if no Open Channel client was installed on operating on the
mobile device. Accordingly, the total virtual time is always equal
to or greater than the actual time calculated with respect to the
example of FIG. 11A and FIG. 11B.
[0453] With reference to the example of FIG. 12A and FIG. 12B, the
table 5 below indicates the relevant portions of the example input
net log and input radio log (collectively, input log).
TABLE-US-00005 TABLE 5 Input Net log fields RL1 07:26:00.000
data_activity_connected data_activity_dormant Virtual Radio up
.uparw. NL1 07:26:00.500 0 0 0 0 323 653 mobile_gprs NL2
07:26:20.000 0 0 0 0 23 432 mobile_gprs NL3 07:27:00.100 32 234 423
234 0 0 mobile_gprs RL2 07:30:00.000 data_activity_dormant
data_activity_connected Virtual Radio down .dwnarw. NL4
07:31:00.000 45 34 0 0 0 0 mobile_gprs Virtual radio up .uparw. NL5
07:31:01.500 45 234 0 0 0 0 mobile_gprs DL 07:31:16.500 No this
record in input. It is only for illustrating purpose here. Virtual
Radio down .dwnarw. after dormancy (network) delay of 15 sec
[0454] In some embodiments, the DL record is not a part of (an item
in) the input log. As indicated above, the input net log and input
radio log each include various net log items. As discussed herein,
the net log items are indicated by the connotation "NLx" while the
radio log items are indicated using the "RLx" connotation.
[0455] As shown in this example, the analysis core tool calculates
an actual connection field (or flag) and actual time field for each
net log item. An example output table 6 is illustrated below.
TABLE-US-00006 TABLE 6 Output Net log fields TimeStamp Virtual
connection Virtual Time NL1 07:26:00.500 1 20 000 NL2 07:26:20.000
0 40 000 NL3 07:27:00.000 0 180 000 NL4 07:31:00.000 1 1 500 NL5
07:31:01.500 0 15 000 TOTAL 2 256 500
[0456] In this example, RL1 is calculated to be the first virtual
radio up log item or entry because real radio up actually occurs.
RL2 is calculated to be the first radio down log because real radio
down actually occurs. NL4 is calculated to be the second virtual
radio up log because "CLIENT_BYTES_IN" or "CLIENT_BYTES_OUT" are
greater than zero. That is, at NL4 data was transferred between OC
client and the OC server. DL is calculated to be the second radio
down log because exactly at DL, the network delay ends. Also, in
this example, NL5 is not calculated to be a virtual radio up in the
log because the time interval between NL4 and NL5 is less than
dormancy.
[0457] With respect to the virtual connection field calculation,
NL1 makes a virtual connection because it makes actual connection.
NL4 makes a virtual connection because it makes virtual radio up.
Therefore: [0458] Virtual connection NL1=1 [0459] Virtual
connection NL2=0 [0460] Virtual connection NL3=0 [0461] Virtual
connection NL4=1 [0462] Virtual connection NL5=0 With respect to
the virtual time field calculations: [0463] Virtual time NL1=Actual
time NL1 [0464] Virtual time NL2=Actual time NL2 [0465] Virtual
time NL3=Actual time NL3 [0466] Virtual time NL4=[NL4, NL5] [0467]
Virtual time NL5=[NL5, DL] where, [0468] [NL4, NL5] is time
interval between net log item NL4 and net log item NL5 [0469] [NL5,
DL] is time interval between net log item NL5 and virtual radio
down item DL and, [0470] [NL4, NL5]=07:31:01.500-07:31:00.000=1 500
[0471] [NL1, NL2]=07:31:16.500-07:31:01.500=15 000 Here DL is time
when network delay happens starting from virtual radio up. Thus,
[0472] Virtual time NL1=20 000 [0473] Virtual time NL2=40 000
[0474] Virtual time NL3=180 000 [0475] Virtual time NL4=1 500
[0476] Virtual time NL5=15 000
Therefore,
[0476] [0477] Total Virtual Time=Total Actual Time+dormancy
(network delay) [0478] Total Virtual Time=240 000+16 500=256 500
[0479] Virtual time NL1=20 000 [0480] Virtual time NL2=40 000
[0481] Virtual time NL3=180 000 [0482] Virtual time NL4=1 500
[0483] Virtual time NL5=15 000
Example Simulated Fields Calculations
[0484] Referring next to FIG. 13A and FIG. 13B which illustrate
example operation for calculation of a simulated radio up interval
and graphical illustration of an example simulated radio up
interval, respectively. More specifically, the simulated fields
calculations include calculations of simulated connection fields
and a simulated time connected fields.
[0485] In one embodiment, a analysis core tool or module (not
shown) can calculate expanded fields that are maintained and
utilized by the analysis core tool to model signaling of a mobile
device in a mobile network. More specifically, the analysis core
tool can model the effects of the Open Channel architecture (e.g.,
the distributed caching techniques including the Signal
Optimization and Extended Caching techniques discussed herein). For
example, the analysis core tool or module such as, for example,
analysis core 255a of FIG. 2E or CRSC analysis core 375a of FIG.
3E, can calculate simulated radio up intervals. The calculation can
include calculating one or more additional fields based on one or
more input logs (e.g., traffic activity log including network hit
information).
[0486] More specifically, as shown in the example of FIG. 13B, the
analysis core tool or module utilizes the networkHit netLogs to
calculate the simulated radio up intervals.
[0487] To calculate simulated fields one the system assumes that
all applications in mobile device use Open Channel client and there
is no application that can start connection without Open Channel.
Radio log for that situation is called simulated radio log. The
simulated connection field indicates a connection that would happen
through network if there were no other application on phone instead
of those which are under control of Open Channel client. Similarly,
the simulated time fields indicate the time of connection that
would happen through network if there were no other application on
phone instead of those which are under control of Open Channel
client.
[0488] With reference to the example of FIG. 13A and FIG. 13B, the
table 7 below indicates the relevant portions of the input traffic
activity log including network hits. In some embodiments, the real
(actual) radio logs can be ignored when calculating the simulated
radio up intervals. Accordingly, the real (actual) radio log items
are not shown in the input table data below.
TABLE-US-00007 TABLE 7 Input Net log fields NL1 07:26:00.500 32 234
23 42 0 0 mobile_gprs Simulated Radio up .uparw. DL1 07:26:15.500
No this record in input. It is only for illustrating purpose
Simulated Radio down here. .dwnarw. after dormancy (network) delay
of 15 sec NL2 07:26:20.000 43 23 342 424 0 0 mobile_gprs Simulated
Radio up .uparw. DL2 07:26:35.000 No this record in input. It is
only for illustrating purpose Simulated Radio down here. .dwnarw.
after dormancy (network) delay of 15 sec NL3 07:27:00.000 32 234
423 234 0 0 mobile_gprs Simulated Radio up .uparw. DL3 07:27:15.000
No this record in input. It is only for illustrating purpose
Simulated Radio down here. .dwnarw. after dormancy (network) delay
of 15 sec
[0489] In this example, the DL1, DL2, and DL3 records (or items)
are not inputs. Rather, the records are illustrated for clarity of
description purposes. As discussed herein, the net log items are
indicated by the connotation "NLx."
[0490] The analysis core tool such as, for example, analysis core
255a of FIG. 2E or CRSC analysis core 375a of FIG. 3E processes the
input log(s) to, for example, calculate one or more additional
fields based on the one or more input logs (e.g., the traffic
activity log). This process can include utilizing one or more long
poll techniques to split one net log item into two or more net log
items. This process is illustrated and discussed in greater detail
with reference to FIG. 19A. As shown in this example, the analysis
core tool calculates simulated connection fields (or flags) and
simulated time fields. An example output table 8 illustrating
output net log fields is illustrated below.
TABLE-US-00008 TABLE 8 Output Net log fields TimeStamp Simulated
connection Simulated Time NL1 07:26:00.500 1 15 000 NL2
07:26:20.000 1 15 000 NL3 07:27:00.000 1 15 000 TOTAL 3 45 000
[0491] In this example, NL1 is the first simulated radio up log
because net log item starts here. DL1 is the first simulated radio
down log because exactly at that time network delay ends. NL2 is
the second simulated radio up log for the same reason as NL1. DL2
is the second simulated radio down for the same reason as RL1. NL3
is the third simulated radio up log for the same reason as NL1. DL3
is the third simulated radio down log for the same reason as
RL1.
[0492] With respect to the simulated connection fields
calculations, NL1, NL2, and NL3 make a simulated connection because
each causes a simulated radio up even. Therefore,
[0493] Simulated connection NL1=1;
[0494] Simulated connection NL2=1;
[0495] Simulated connection NL3=1.
[0496] With respect to the simulated time fields calculations, if
the time interval between two adjacent net log items is greater
than dormancy, then the first net log item will have simulated time
equal to dormancy. Otherwise, the time interval between the two
adjacent net log items will be the actual time between the net log
items. An example is illustrated in FIG. 13C.
[0497] Therefore, in the example of FIG. 13A-13C
[0498] Simulated time NL1=dormancy (network delay)=15 000
[0499] Simulated time NL2=dormancy (network delay)=15 000
[0500] Simulated time NL3=dormancy (network delay)=15 000
Example Virtual Simulated Fields Calculations
[0501] FIGS. 14A and 14B illustrate an example architecture for
calculation of a virtual simulated radio up interval and
illustration of an example virtual simulated radio time interval,
respectively. More specifically, the virtual simulated fields
calculation described below incudes calculation of a virtual
simulated field and a virtual simulated time connected field.
[0502] In one embodiment, a analysis core tool or module (not
shown) can calculate expanded fields that are maintained and
utilized by the analysis core tool to model signaling of a mobile
device in a mobile network. More specifically, the analysis core
tool can model the effects of the Open Channel architecture (e.g.,
the distributed caching techniques including the Signal
Optimization and Extended Caching techniques discussed herein). For
example, the analysis core tool or module such as, for example,
analysis core 255a of FIG. 2E or CRSC analysis core 375a of FIG.
3E, can calculate simulated virtual radio up intervals. The
calculation can include calculating one or more additional fields
based on one or more input logs (e.g., radio log and a traffic
activity log including network hit and cache hit information).
[0503] More specifically, as shown in the example of FIG. 14B, the
analysis core tool or module utilizes a networkHit and a cacheHit
netLogs to calculate the simulated virtual radio up intervals. As
discussed herein, the radio up (or active) intervals
[0504] The simulated virtual fields indicate the connections that
happen in a simulated environment in which all applications on the
mobile device that normally use the Open Channel client are
simulated but there is no Open Channel on the mobile device.
[0505] The simulated virtual connection fields indicate the
connection(s) that would occur through the network in a simulated
environment in which all applications on the mobile device that
normally use the Open Channel client are simulated but there is no
Open Channel on the mobile device. Similarly, the simulated virtual
time fields indicate the time connected from the connections that
would occur through network in a simulated environment in which all
applications on the mobile device that normally use the Open
Channel client are simulated but there is no Open Channel on the
mobile device.
[0506] With reference to the example of FIG. 14A and FIG. 14B, the
table 9 below indicates the relevant portions of the input log
including network hits. In a simulated environment in which all
applications on the mobile device that normally use the Open
Channel client are simulated but there is no Open Channel on the
mobile device.
TABLE-US-00009 TABLE 9 Input Net log fields NL1 07:26:00.500 32 234
23 42 0 0 mobile_gprs Simulated Radio up .uparw. DL1 07:26:16.000
No this record in input. It is only for Simulated Radio down
illustrating purpose here. .dwnarw. after dormancy (network) delay
of 15 sec NL2 07:26:20.000 43 23 342 424 0 0 mobile_gprs Simulated
Radio up .uparw. DL2 07:26:35.000 No this record in input. It is
only for Simulated Radio down illustrating purpose here. .dwnarw.
after dormancy (network) delay of 15 sec NL3 07:27:00.000 32 234
423 234 0 0 mobile_gprs Simulated Radio up .uparw. DL3 07:27:15.000
No this record in input. It is only Simulated Radio down for
illustrating purpose here. .dwnarw. after dormancy (network) delay
of 15 sec NL4 07:31:00.000 45 34 0 0 0 0 mobile_gprs Simulated
Virtual radio up .uparw. NL5 07:31:01.500 45 234 0 0 0 0
mobile_gprs DL4 07:32:16.500 No this record in input. It is only
Simulated Virtual for illustrating purpose here. Radio down
.dwnarw. after dormancy (network) delay of 15 sec
[0507] In this example, the DL1, DL2, and DL3 records (or items)
are not inputs. Rather, these records are illustrated for clarity
of description purposes. As discussed herein, the net log items are
indicated by the connotation "NLx."
[0508] The analysis core tool such as, for example, analysis core
255a of FIG. 2E or CRSC analysis core 375a of FIG. 3E processes the
input log(s) to, for example, calculate one or more additional
fields based on the one or more input logs (e.g., the traffic
activity log). This process can include utilizing one or more long
poll techniques to split one net log item into two or more net log
items. This process is illustrated and discussed in greater detail
with reference to FIG. 19A. As shown in this example, the analysis
core tool calculates simulated connection fields (or flags) and
simulated time fields. An example output table 10 illustrating
output net log fields is illustrated below.
TABLE-US-00010 TABLE 10 Output Net log fields Simulated virtual
TimeStamp connection Simulated virtual Time NL1 07:26:00.500 1 15
000 NL2 07:26:20.000 1 15 000 NL3 07:27:00.000 1 15 000 NL4
07:31:00.000 1 1 500 NL5 07:31:01.500 0 15 000 TOTAL 4 61 500
[0509] In this example, NL4 is the fourth simulated virtual radio
up log because "CLIENT_BYTES_IN" or "CLIENT_BYTES_OUT" are greater
than zero indicating that data was transferred between OC client
and OC server. Note that NL5 is not a simulated virtual radio up
log item because time interval between NL4 and NL5 is less than
dormancy.
Example Simulated Per Application Fields Calculations
[0510] FIGS. 15A and 15B illustrate an example architecture for
calculation of simulated radio up intervals and illustration of an
example simulated radio time intervals, respectively. More
specifically, the simulated fields calculation described below
incudes calculation of a virtual simulated field and a virtual
simulated time connected field on a per application basis.
[0511] In one embodiment, a analysis core tool or module (not
shown) can calculate expanded fields that are maintained and
utilized by the analysis core tool to model signaling of a mobile
device in a mobile network. More specifically, the analysis core
tool can model the effects of the Open Channel architecture (e.g.,
the distributed caching techniques including the Signal
Optimization and Extended Caching techniques discussed herein). For
example, the analysis core tool or module such as, for example,
analysis core 255a of FIG. 2E or CRSC analysis core 375a of FIG.
3E, can calculate simulated radio up intervals on a per application
basis. The calculation can include calculating one or more
additional fields based on one or more input logs (e.g., traffic
activity log including network hit information).
[0512] More specifically, as shown in the example of FIG. 15B, the
analysis core tool or module utilizes the netLogs of certain
applications to calculate simulated per application radio up
intervals. In the example of FIG. 15B, netlog NL1 is associated
with a first application #1 and netlogs NL2 and NL3 are associated
with a second application #2.
[0513] In the example of FIG. 15C, the simulated radio up interval
per the first application #1 is illustrated. Similarly, the example
of FIG. 15D illustrates the simulated radio up intervals per the
second application #2.
[0514] The simulated per application fields indicate connections
that happen in a simulated environment in which all applications on
the mobile device that normally use the Open Channel client are
simulated but there is no Open Channel on the mobile device. To
calculate simulated per application fields the system contemplates
only one application (e.g., Application #1) on the mobile device.
The one application (e.g., Application #1) utilizes the Open
Channel client and there is no application that can start
connection without Open Channel. The radio log for this situation
is called simulated per application radio log.
[0515] The simulated per application connection is a connection
that would happen through the network if there were one application
installed on a mobile device (under the control of Open Channel
client) and no other applications on phone. Similarly, the
simulated per application time is time of connection that would
happen through network if there were one application installed on
the mobile device (under control of Open Channel client) and no
other applications on phone.
[0516] With reference to the example of FIG. 15A and FIG. 15B, the
table 11 below indicates the relevant portions of the input log
including network hits. While calculating simulated radio up
intervals we ignore real (actual) radio logs, that is why they are
not shown in input data. See example in table 11.
TABLE-US-00011 TABLE 11 Input Net log fields NL1 07:26:00.500 32
234 23 42 0 0 mobile_gprs App1 Simulated Radio up .uparw. DL1
07:26:15.500 No this record in input. It is only for Simulated
Radio down .dwnarw. illustrating purpose here. after dormancy
(network) delay of 15 sec NL2 07:26:20.000 43 23 342 424 0 0
mobile_gprs App2 Simulated Radio up .uparw. DL2 07:26:35.000 No
this record in input. It is only Simulated Radio down .dwnarw. for
illustrating purpose here. after dormancy (network) delay of 15 sec
NL3 07:27:00.000 32 234 423 234 0 0 mobile_gprs App2 Simulated
Radio up .uparw. DL3 07:27:15.000 No this record in input. It is
only Simulated Radio down .dwnarw. for illustrating purpose here.
after dormancy (network) delay of 15 sec
[0517] In this example, the DL1, DL2, and DL3 records (or items)
are not inputs. Rather, these records are illustrated for clarity
of description purposes. As discussed herein, the net log items are
indicated by the connotation "NLx."
[0518] The analysis core tool such as, for example, analysis core
255a of FIG. 2E or CRSC analysis core 375a of FIG. 3E processes the
input log(s) to, for example, calculate one or more additional
fields based on the one or more input logs (e.g., the traffic
activity log). This process can include utilizing one or more long
poll techniques to split one net log item into two or more net log
items. This process is illustrated and discussed in greater detail
with reference to FIG. 19A. As shown in this example, the analysis
core tool calculates simulated per application connection fields
(or flags) and simulated per application time fields. An example
output table 12 illustrating output net log fields is illustrated
below.
TABLE-US-00012 TABLE 12 Output Net log fields Simulated per App
TimeStamp connection Simulated per App Time NL1 07:26:00.500 1 15
000 NL2 07:26:20.000 1 15 000 NL3 07:27:00.000 1 15 000 TOTAL 3 45
000
[0519] In this example, NL1 is the first simulated radio up log
because net log item starts here. DL1 is the first simulated radio
down log because exactly at that time network delay ends. NL2 is
the second simulated radio up log for the same reason as NL1. DL2
is the second simulated radio down for the same reason as RL1. NL3
is the third simulated radio up log for the same reason as NL1. DL3
is the third simulated radio down log for the same reason as
RL1.
[0520] With respect to the simulated per application connection
fields, NL1, NL2, and NL3 make a simulated connection because each
causes a simulated radio up event. Therefore,
[0521] Simulated connection NL1=1
[0522] Simulated connection NL2=1
[0523] Simulated connection NL3=1 and,
[0524] Simulated time NL1=dormancy (network delay)=15 000
[0525] Simulated time NL2=dormancy (network delay)=15 000
[0526] Simulated time NL3=dormancy (network delay)=15 000
Example Virtual Simulated Per Application Fields Calculations
[0527] FIGS. 16A and 16B illustrate an example architecture for
calculation of a virtual simulated per application radio up
interval and illustration of an example virtual simulated per
application radio time interval, respectively. More specifically,
the virtual simulated per application fields calculations described
below include calculation of a virtual simulated per application
field and a virtual simulated time connected per application
field.
[0528] In one embodiment, a analysis core tool or module (not
shown) can calculate expanded fields that are maintained and
utilized by the analysis core tool to model signaling of a mobile
device in a mobile network. More specifically, the analysis core
tool can model the effects of the Open Channel architecture (e.g.,
the distributed caching techniques including the Signal
Optimization and Extended Caching techniques discussed herein). For
example, the analysis core tool or module such as, for example,
analysis core 255a of FIG. 2E or CRSC analysis core 375a of FIG.
3E, can calculate simulated virtual radio up intervals. The
calculation can include calculating one or more additional fields
based on one or more input logs (e.g., radio log and a traffic
activity log including network hit and cache hit information).
[0529] More specifically, as shown in the example of FIG. 16B, the
analysis core tool or module utilizes a networkHit and a cacheHit
netLogs to calculate the simulated virtual radio up intervals. As
discussed herein, the radio up intervals indicate a period of time
during which the mobile device radio is active.
[0530] In the example of FIG. 16C, the simulated virtual radio up
interval associated with the first application #1 is illustrated.
Similarly, the example of FIG. 16D illustrates the simulated
virtual radio up intervals associated with the second application
#2.
[0531] The simulated virtual per application fields indicate the
connections that happen in a simulated environment in which a
single application on the mobile device that normally uses the Open
Channel client is simulated but there is no Open Channel on the
mobile device.
[0532] The simulated virtual per application connection fields
indicate the connection(s) that would occur through the network in
a simulated environment in which a single application on the mobile
device that normally uses the Open Channel client is simulated but
there is no Open Channel on the mobile device. Similarly, the
simulated virtual time fields indicate the time connected from the
connections that would occur through network in a simulated
environment in which a single application on the mobile device that
normally uses the Open Channel client is simulated but there is no
Open Channel on the mobile device.
[0533] With reference to the example of FIG. 16A and FIG. 16B, the
table 13 below indicates the relevant portions of the input log
including network hits. In a simulated environment in which all
applications on the mobile device that normally use the Open
Channel client are simulated but there is no Open Channel on the
mobile device.
TABLE-US-00013 TABLE 13 Input Net log fields NL1 07:26:00.500 32
234 23 42 0 0 mobile_gprs App1 Simulated Radio up .uparw. DL1
07:26:16.000 No this record in input. It is only for Simulated
Radio down .dwnarw. illustrating purpose here. after dormancy
(network) delay of 15 sec NL2 07:26:20.000 43 23 342 424 0 0
mobile_gprs App2 Simulated Radio up .uparw. DL2 07:26:35.000 No
this record in input. It is only for Simulated Radio down .dwnarw.
illustrating purpose here. after dormancy (network) delay of 15 sec
NL3 07:27:00.000 32 234 423 234 0 0 mobile_gprs App2 Simulated
Radio up .uparw. DL3 07:27:15.000 No this record in input. It is
only for Simulated Radio down .dwnarw. illustrating purpose here.
after dormancy (network) delay of 15 sec NL4 07:31:00.000 45 34 0 0
0 0 mobile_gprs App2 Simulated Virtual radio up .uparw. NL5
07:31:01.500 45 234 0 0 0 0 mobile_gprs App2 DL4 07:32:16.500 No
this record in input. It is only for Simulated Virtual Radio
illustrating purpose here. down .dwnarw. after dormancy (network)
delay of 15 sec
[0534] In this example, DL1, DL2, and DL3 records (or items) are
not inputs. Rather, these records are illustrated for clarity of
description purposes. As discussed herein, the net log items are
indicated by the connotation "NLx."
[0535] The analysis core tool such as, for example, analysis core
255a of FIG. 2E or CRSC analysis core 375a of FIG. 3E processes the
input log(s) to, for example, calculate one or more additional
fields based on the one or more input logs (e.g., the traffic
activity log). This process can include utilizing one or more long
poll techniques to split one net log item into two or more net log
items. This process is illustrated and discussed in greater detail
with reference to FIG. 19A. As shown in this example, the analysis
core tool calculates simulated per application connection fields
(or flags) and simulated per application time fields. An example
output table 14 illustrating output net log fields is illustrated
below.
TABLE-US-00014 TABLE 14 Output Net log fields Simulated virtual per
app Simulated virtual TimeStamp connection per app Time NL1
07:26:00.500 1 15 000 NL2 07:26:20.000 1 15 000 NL3 07:27:00.000 1
15 000 NL4 07:31:00.000 1 1 500 NL5 07:31:01.500 0 15 000 TOTAL 4
61 500
Example Saved Values
[0536] As discussed herein, the various field calculations can be
used to model the signaling in a mobile network. For example, the
modeling can include calculating a saved connections and a saved
time. The saved connections indicate the amount, number, or
quantity of connections that were saved as a result of utilizing
the Open Channel architecture. In one embodiment, the saved
connections can be modeled as follows: [0537] Saved
connection=Virtual connection-Actual connection, [0538] Saved
simulated connection=Simulated virtual connection-Simulated
connection, [0539] Saved simulated per app connection=Simulated
virtual per app connection-Simulated per app connection, [0540]
Saved simulated per host connection=Simulated virtual per host
connection-Simulated per host connection.
[0541] Similarly, the saved time is time interval of connection
time that was saved as a result of utilizing the Open Channel
architecture. In one embodiment, the saved time can be modeled as
follows: [0542] Saved time=Virtual time-Actual time, [0543] Saved
simulated time=Simulated virtual time-Simulated time, [0544] Saved
simulated per app time=Simulated virtual per app time-Simulated per
app time, [0545] Saved simulated per host time=Simulated virtual
per host time-Simulated per host time.
Connection Flags and Time
[0546] FIG. 17A illustrates an example of calculating the
connection flags and connection time intervals discussed above.
Connection flags indicate whether a particular netLog caused radio
up. In one embodiment, to determine the connection flag for each
radio up interval the closest netLog to radio up log record is
marked with connection flag. Importantly, only netlogs that are in
Request Delay neighborhood to Radio Up log are marked with a
connection flag.
[0547] FIG. 17B illustrates an example radio up interval. The radio
up interval may be calculated, maintained, and/or otherwise
obtained to calculate the time connected indicate impact of a
particular netLog on radio up time. For each radio up interval, the
radio up time equals to sum of time connected values for netLogs
that belong to that particular interval.
Network Hits
[0548] A network hit is start point of data transfer at open
channel server side. In one embodiment, a net log item is
considered a network hit when at least one of these conditions of
its associated fields are true:
[0549] SERVER_BYTES_IN>0;
[0550] SERVER_BYTES_OUT>0;
[0551] OPERATION=radio_up; and,
[0552] OPERATION !=proxy_tc_handshake
Cache Hits
[0553] A cache hit is start point of data transfer in cache. In one
embodiment, a net log item is considered a cache hit when it is not
net log hit and at least one of these conditions of its associated
fields are true:
[0554] CLIENT_BYTES_IN>0
[0555] CLIENT_BYTES_OUT>0
[0556] OPERATION=deferred_app_close; and,
[0557] OPERATION !=proxy_https_handshake
Detailed Example Calculation
[0558] The following example illustrates another field calculation.
To begin, suppose the following input netlog and radio log:
TABLE-US-00015 TABLE 15 Input Net log fields Client Client Server
Server Cache Cache bytes bytes bytes bytes bytes bytes # Timestamp
in out in out in in Interface 1 07:26:00.000 111 111 0 0 0 0
mobile_gprs 2 07:26:20.000 111 111 0 0 0 0 mobile_gprs 3
07:27:00.100 32 234 423 234 0 0 mobile_gprs 4 07:29:00.000 432 63
476 73 0 0 mobile_gprs 5 07:29:00.500 234 32 23 261 0 0 mobile_gprs
6 07:31:00.000 111 111 0 0 0 0 mobile_gprs
TABLE-US-00016 TABLE 16 Input Radio log fields # Timestamp State
Prev state 1 07:27:00.000 data_activity_connected
data_activity_dormant 2 07:30:00.000 data_activity_dormant
data_activity_connected
[0559] FIG. 18 depicts an example scheme illustrating logs over a
period of time. For example, assume [0560]
t1=(07:26:20.000-07:26:00.000)=20 000 ms, [0561]
t2=(07:27:00.000-07:26:20.000)=40 000 ms, [0562]
t3=(07:27:00.100-07:27:00.000)=100 ms, [0563]
t4=(07:29:00.000-07:27:00.100)=119 000 ms, [0564]
t5=(07:29:00.500-07:29:00.000)=500 ms, [0565]
t6=(07:30:00.000-07:29:00.500)=59 500 ms, [0566]
t7=(07:31:00.000-07:30:00.000)=60 000 ms, and network delay=15 sec,
thus, [0567] t1, (t2+t3), t4, (t6+t7)>network delay; and [0568]
t5<network delay; [0569] t3<request delay.
[0570] Table 17, below, illustrates the results of the
calculation
TABLE-US-00017 TABLE 17 Result calculation Parameter, log-item 1 2
3 4 5 6 Actual conn 0 0 1 0 0 0 Virtual conn 1 1 1 0 0 1 Actual
time 0 0 t3 + t4 t5 t6 0 Virtual time Network Network t3 + t4 t5 t6
Network delay delay delay
[0571] Table 18 indicates the output net log description. Note that
the output time intervals are in milliseconds.
TABLE-US-00018 TABLE 18 output net log Actual Virtual Actual
Virtual Saved Saved # Timestamp conn conn time time conn time 1
07:26:00.000 0 1 0 15000 1 15000 2 07:26:20.000 0 1 0 15000 1 15000
3 07:28:00.000 1 1 120000 120000 0 0 4 07:29:00.000 0 0 500 500 0 0
5 07:29:01.000 0 0 59500 59500 0 0 6 07:31:00.000 0 1 0 15000 1
15000
Example Long Poll Procedure
[0572] FIG. 19A graphically illustrates a long poll procedure for
splitting one netlog item into two netlog items, according to an
embodiment. More specifically, the Long poll procedure described
herein is the process of splitting one netlog item into two netlog
items. In one embodiment, the conditions for performing a long poll
procedure for netlog item are: [0573] RESPONSE_TIME is greater than
or equals to network delay (default, e.g., 15 000 ms); [0574]
Netlog item is network hit or cache hit; [0575] Value of
SERVER_BYTES_IN/RESPONSE_TIME is less than or equals to split ratio
(default, e.g., 3 000 ms).
[0576] FIG. 19B graphically illustrates the conditions which must
be true in order for the netlog to be split in two parts. More
specifically, if the value of SERVER_BYTES_IN/RESPONSE_TIME is less
than or equals to split ratio (default, e.g., 3 000 ms) then the
netlog can be split in two parts. The table 19 below illustrates
the field modifications occurring as a result of performing the
long poll procedure.
TABLE-US-00019 TABLE 19 fields changing after long poll procedure
Source netlog Netlog after splitting Added netlog TIMESTAMP =>
TIMESTAMP TIMESTAMP + RESPONSE_TIME CLIENT_BYTES_IN CLIENT_BYTES_IN
0 CLIENT_BYTES_OUT 0 CLIENT_BYTES_OUT SERVER_BYTES_IN 0
SERVER_BYTES_IN SERVER_BYTES_OUT SERVER_BYTES_OUT 0 CACHED_BYTES_IN
0 CACHED_BYTES_IN CACHED_BYTES_OUT 0 CACHED_BYTES_OUT RESPONSE_TIME
0 0 Other fields The same as in source The same as in source
[0577] Example input and output net logs, pre- and post-split,
respectively, are illustrated below.
TABLE-US-00020 TABLE 20 Input Net log and Radio fields RL1
07:26:00.000 data_activity_connected data_activity_dormant Radio up
.uparw. NL1 07:26:00.500 32 234 23 42 0 0 mobile_gprs 27 RL2
07:30:00.000 data_activity_dormant data_activity_connected Radio
down .dwnarw.
TABLE-US-00021 TABLE 21 Output Net log and Radio fields RL1
07:26:00.000 data_activity_connected data_activity_dormant Radio up
.uparw. NL1 07:26:00.500 32 0 0 42 0 0 mobile_gprs 0 NL2
07:26:27.500 0 234 23 0 0 0 mobile_gprs 0 RL2 07:30:00.000
data_activity_dormant data_activity_connected Radio down
.dwnarw.
Example Log Preprocessing
[0578] In some embodiments, log preprocessing is performed before
the data in the calculated fields is populated. For example, the
following procedures can be performed:
[0579] If [0580] Operation is PROXY_HTTPS_HANDSHAKE; and [0581]
CLIENT_BYTES_IN>0 or CLIENT_BYTES_OUT>0; and [0582]
SERVER_BYTES_IN>0 or SERVER_BYTES_OUT>0;
[0583] Then replace CLIENT_BYTES_OUT with SERVER_BYTES_IN.
[0584] If [0585] Operation is PROXY_CACHEABLE_APP_COMPRESSED; or
[0586] Operation is PROXY_UNCACHEABLE_APP_COMPRESSED; and [0587]
SERVER_BYTES_IN>0;
[0588] Then replace CLIENT_BYTES_OUT with SERVER_BYTES_IN.
[0589] If [0590] Operation is PROXY_CACHEABLE_APP_COMPRESSED; or
[0591] Operation is PROXY_UNCACHEABLE_APP_COMPRESSED; and [0592]
SERVER_BYTES_OUT>0;
[0593] Then replace CLIENT_BYTES_IN with SERVER_BYTES_OUT.
[0594] If [0595] CLIENT_BYTES_IN>0; and [0596]
CLIENT_BYTES_OUT==0; and [0597] SERVER_BYTES_IN==0; and [0598]
SERVER_BYTES_OUT==0;
[0599] Then replace CLIENT_BYTES_IN with zero value.
[0600] If RESPONSE_TIME<0 then replace RESPONSE_TIME with zero
value.
Report Processing
[0601] Various example field calculations are now described.
[0602] Example Time on not Charging Calculation
[0603] FIG. 20 graphically illustrates an example calculation of
the TIME_ON_NOT_CHARGING field. In some embodiments, a power log
can be used to make the calculation. In some embodiments, the
TIME_ON_NOT_CHARGING field represents a sum of intervals when a
device's battery health was decreasing. For example,
TIME_ON_NOT_CHARGING=[Battery interval 1]+[Battery interval 2].
[0604] Example Charge Drop Percent Calculation
[0605] FIG. 21 graphically illustrates an example calculation of
the CHARGE_DROP_PERCENT field. Again, a power log can be used to
make the calculation. In some embodiments, the Drop percent
represents a sum of changes of battery health when battery health
is decreasing. For example,
CHARGE_DROP_PERCENT=[89-25]+[60-10]=64+50=114 (percent).
[0606] Example Time Radio State Calculation
[0607] The table 22 below describes the relationship between
various example previous radio states and corresponding report
fields. More specifically, the table below describes the
TIME_RADIO_STATE_n field calculation, where n runs from 1 to 10. In
this example, a radio log is used and if the value of INTERVAL in
the radio log is greater than zero, then the value of INTERVAL
field is saved into one of the TIME_RADIO_STATE_n fields.
TABLE-US-00022 TABLE 22 Correspondence between previous radio
states and report fields # Previous radio state Report field 1
DATA_ACTIVITY_CONNECTED TIME_RADIO_STATE_1 2 DATA_ACTIVITY_DORMANT
TIME_RADIO_STATE_2 3 DATA_CONNECTED TIME_RADIO_STATE_3 4
DATA_CONNECTING TIME_RADIO_STATE_4 5 DATA_DISCONNECTED
TIME_RADIO_STATE_5 6 DATA_SUSPENDED TIME_RADIO_STATE_6 7
STATE_EMERGENCY_ONLY TIME_RADIO_STATE_7 8 STATE_IN_SERVICE
TIME_RADIO_STATE_8 9 STATE_OUT_OF_SERVICE TIME_RADIO_STATE_9 10
STATE_POWER_OFF TIME_RADIO_STATE_10
[0608] Example Transition into Radio State Calculation
[0609] The table 23 below describes the TRANS_INTO_RADIO_STATE_n
field, where n runs from 1 to 10. In this example, a radio log is
used. The TRANS_INTO_RADIO_STATE_n field represents the number of
times a radio log has transitioned into certain state.
TABLE-US-00023 TABLE 23 Correspondence between current radio states
and report fields Report field (how many times # Current radio
state radio was in this state) 1 DATA_ACTIVITY_CONNECTED
TRANS_INTO_RADIO_STATE_1 2 DATA_ACTIVITY_DORMANT
TRANS_INTO_RADIO_STATE_2 3 DATA_CONNECTED TRANS_INTO_RADIO_STATE_3
4 DATA_CONNECTING TRANS_INTO_RADIO_STATE_4 5 DATA_DISCONNECTED
TRANS_INTO_RADIO_STATE_5 6 DATA_SUSPENDED TRANS_INTO_RADIO_STATE_6
7 STATE_EMERGENCY_ONLY TRANS_INTO_RADIO_STATE_7 8 STATE_IN_SERVICE
TRANS_INTO_RADIO_STATE_8 9 STATE_OUT_OF_SERVICE
TRANS_INTO_RADIO_STATE_9 10 STATE_POWER_OFF
TRANS_INTO_RADIO_STATE_10
[0610] Example WCDMA Time Calculation
[0611] The table 24 below describes the WCDMA_TIME_IN_DCH,
WCDMA_TIME_IN_FACH, WCDMA_TIME_IN_PCH, and WCDMA_TIME_IN_IDLE
fields. Again, a radio log is used in this example and if the value
of INTERVAL in the radio log is greater than zero, then the value
of the INTERVAL field is saved into one of fields WCDMA_TIME_< .
. . >fields. The correspondence between previous radio states
and report fields is shown in the table below.
TABLE-US-00024 TABLE 24 Correspondence between previous radio
states and report fields # Previous radio state Report field 1
CELL_DCH WCDMA_TIME_IN_DCH 2 CELL_PCH WCDMA_TIME_IN_PCH 3 CELL_FACH
WCDMA_TIME_IN_FACH 4 IDLE WCDMA_TIME_IN_IDLE
[0612] Example WCDMA Transition into Radio State Calculation
[0613] The table 25 below describes the WCDMA_TRANS_INTO_DCH,
WCDMA_TRANS.sub.-- INTO_FACH, WCDMA_TRANS_INTO_PCH,
WCDMA_TRANS_INTO_IDLE calculation fields. The radio log is used in
this example. Field WCDMA_TRANS_INTO_< . . . >indicates how
many times radio log has transition into certain state.
TABLE-US-00025 TABLE 25 Correspondence between current radio states
and report fields Report field (how many times # Current radio
state radio was in this state) 1 CELL_DCH WCDMA_TRANS_INTO_DCH 2
CELL_PCH WCDMA_TRANS_INTO_PCH 3 CELL_FACH WCDMA_TRANS_INTO_FACH 4
IDLE WCDMA_TRANS_INTO_IDLE
[0614] Example Total Bytes Calculation
[0615] The table 26 below describes the TOTAL_BYTES_FROM_APP,
TOTAL_BYTES_TO_APP, TOTAL_BYTES_FROM_NET, TOTAL_BYTES_TO_NET,
TOTAL_BYTES_FROM_CACHE, TOTAL_BYTES_TO_CACHE calculation
fields.
TABLE-US-00026 TABLE 26 Bytes calculation # Field in report Field
from net log used for Comment 1 TOTAL_BYTES_FROM_APP
CLIENT_BYTES_IN Just copy value from net log 2 TOTAL_BYTES_TO_APP
CLIENT_BYTES_OUT 3 TOTAL_BYTES_FROM_NET SERVER_BYTES_IN 4
TOTAL_BYTES_TO_NET SERVER_BYTES_OUT 5 TOTAL_BYTES_FROM_CACHE
CACHED_BYTES_IN 6 TOTAL_BYTES_TO_CACHE CACHED_BYTES_OUT
[0616] Example Total Hits Calculation
[0617] The table below 27 describes the TOTAL_HITS_FROM_APP,
TOTAL_HITS_TO_APP, TOTAL_HITS_FROM_NET, TOTAL_HITS_TO_NET,
TOTAL_HITS_FROM_CACHE, and TOTAL_HITS_TO_CACHE calculation
fields.
TABLE-US-00027 TABLE 27 Hits calculation # Field in report Field
from net log used for Comment 1 TOTAL_HITS_FROM_APP CLIENT_BYTES_IN
1 if CLIENT_BYTES_IN > 0, 0 2 TOTAL_HITS_TO_APP CLIENT_BYTES_OUT
1 if CLIENT_BYTES_OUT > 0, 0 3 TOTAL_HITS_FROM_NET
SERVER_BYTES_IN, 1 if SERVER_BYTES_IN > 0 or 4 TOTAL_HITS_TO_NET
SERVER_BYTES_OUT 1 if SERVER_BYTES_OUT > 0, 0 5
TOTAL_HITS_FROM_CACHE CACHED_BYTES_IN 1 if CACHED_BYTES_IN > 0,
0 6 TOTAL_HITS_TO_CACHE CACHED_BYTES_OUT 1 if CACHED_BYTES_OUT >
0, 0
[0618] Example Cache Requests. Bytes and Hits.
[0619] Table 28 below describes the TOTAL_BYTES_CACHE_REQ and
TOTAL_HITS_CACHE_REQ calculation fields.
TABLE-US-00028 TABLE 28 Cache request calculation # Field in report
Field from net log used for Comment 1 TOTAL_BYTES_CACHE_REQ
CLIENT_BYTES_IN, CLIENT_BYTES_IN if 2 TOTAL_HIITS_CACHE_REQ
CLIENT_BYTES_IN, 1 if CLIENT_BYTES_IN > 0 and
[0620] Example Connections Calculation
[0621] Table 29 below describes the SIM_RADIO_STATE_CHANGES_ACTUAL
and SIM_RADIO_STATE_CHANGES_SAVED calculation fields. In some
embodiments, the net log fields can be used to calculate these
report fields. There are two cases in calculation: [0622] Report
key category is "Application"; [0623] Report key category is other
(not "Application")
[0624] Example Report Key Category is "Application"
TABLE-US-00029 TABLE 30 Connections calculation # Field in report
Field from net log used for Comment 1
SIM_RADIO_STATE_CHANGES_ACTUAL SIM_ACTUAL_CONN_PER_APP Just copy
value 2 SIM_RADIO_STATE_CHANGES_SAVED SIM_SAVED_CONN_PER_APP
[0625] Example Report Key Category is Other (not "Application")
TABLE-US-00030 TABLE 31 Connections calculation # Field in report
Field from net log used Comment 1 SIM_RADIO_STATE_CHANGES_ACTUAL
ACTUAL_CONN Just copy value from net 2
SIM_RADIO_STATE_CHANGES_SAVED SAVED_CONN
[0626] Example Time Calculation
[0627] Table 32 below describes the SIM_RADIO_TIME_CONN_ACTUAL and
SIM_RADIO_TIME_CONN_SAVED calculation fields. In some embodiments,
the net log fields are used to calculate these report fields. There
are two cases in calculation: [0628] Report key category is
"Application"; [0629] Report key category is other (not
"Application")
[0630] Example Report Key Category is "Application"
TABLE-US-00031 TABLE 33 Time calculation # Field in report Field
from net log used for Comment 1 SIM_RADIO_TIME_CONN_ACTUAL
SIM_ACTUAL_TIME_PER_APP Just copy value from net 2
SIM_RADIO_TIME_CONN_SAVED SIM_SAVED_TIME_PER_APP
[0631] Example Report Key Category is Other (not "Application")
TABLE-US-00032 TABLE 34 Time calculation # Field in report Field
from net log used Comment 1 SIM_RADIO_TIME_CONN_ACTUAL ACTUAL_TIME
Just copy value from net log 2 SIM_RADIO_TIME_CONN_SAVED
SAVED_TIME
[0632] Example Netlog Fields
TABLE-US-00033 TABLE 35 Net Log format # Name Type Derived 1
TIMESTAMP TIMEST N 2 CLIENT_Z7TP_ADDRESS STRING N 3
TRANSACTION_TYPE STRING N 4 VERSION_ID INT N 5 CLIENT_BYTES_IN LONG
N 6 CLIENT_BYTES_OUT LONG N 7 SERVER_BYTES_IN LONG N 8
SERVER_BYTES_OUT LONG N 9 CACHE_BYTES_IN LONG N 10 CACHE_BYTES_OUT
LONG N 11 HOST STRING N 12 APPLICATION STRING N 13 APP_STATUS
STRING N 14 OPERATION STRING N 15 PROTOCOL STRING N 16 INTERFACE
STRING N 17 RESPONSE_TIME LONG N 18 REQUEST_ID LONG N 19
STATUS_CODE INT N 20 ERROR_CODE INT N 21 CONTENT_TYPE STRING N 22
HEADER_LENGTH INT N 23 CONTENT_LENGTH LONG N 24 REQUEST_HASH STRING
N 25 RESPONSE_HASH STRING N 26 ANALYSIS STRING N 27 OPTIMIZATION
INT N 28 DESTINATION_PORT INT N 29 SUBSCRIPTION_ID INT N 30 PAYLOAD
STRING N 31 VIRTUAL_CONN INT Y 32 ACTUAL_CONN INT Y 33 SAVED_CONN
INT Y 34 VIRTUAL_TIME LONG Y 35 ACTUAL_TIME LONG Y 36 SAVED_TIME
LONG Y 37 SIM_VIRTUAL_CONN INT Y 38 SIM_ACTUAL_CONN INT Y 39
SIM_SAVED_CONN INT Y 40 SIM_VIRTUAL_TIME LONG Y 41 SIM_ACTUAL_TIME
LONG Y 42 SIM_SAVED_TIME LONG Y 43 SIM_VIRTUAL_CONN_PER.sub.-- INT
Y 44 SIM_ACTUAL_CONN_PER.sub.-- INT Y 45 SIM_SAVED_CONN_PER_AP INT
Y 46 SIM_VIRTUAL_TIME_PER.sub.-- LONG Y 47 SIM_ACTUAL_TIME_PER_A
LONG Y 48 SIM_SAVED_TIME_PER_AP LONG Y 49
SIM_VIRTUAL_CONN_PER.sub.-- INT Y 50 SIM_ACTUAL_CONNECTIO INT Y 51
SIM_SAVED_CONN_PER_H INT Y 52 SIM_VIRTUAL_TIME_PER.sub.-- LONG Y 53
SIM_ACTUAL_TIME_PER_H LONG Y 54 SIM_SAVED_TIME_PER_HO LONG Y
[0633] Example Report format fields
TABLE-US-00034 TABLE 36 report format # Name Type Derived 1
TIMESTAMP TIMESTAMP N 2 LOCAL_TIMESTAMP TIMESTAMP N 3 ENTITY_ID
STRING N 4 BEARER_TYPE INT N 5 CATEGORY_TYPE INT N 6 CATEGORY_VALUE
STRING N 7 TOTAL_BYTES_TO_APP LONG Y 8 TOTAL_BYTES_FROM_APP LONG Y
9 TOTAL_BYTES_TO_CACHE LONG Y 10 TOTAL_BYTES_FROM_CACHE LONG Y 11
TOTAL_BYTES_TO_NET LONG Y 12 TOTAL_BYTES_FROM_NET LONG Y 13
TOTAL_BYTES_CACHE_REQ LONG Y 14 TOTAL_HITS_TO_APP INT Y 15
TOTAL_HITS_FROM_APP INT Y 16 TOTAL_HITS_TO_CACHE INT Y 17
TOTAL_HITS_FROM_CACHE INT Y 18 TOTAL_HITS_TO_NET INT Y 19
TOTAL_HITS_FROM_NET INT Y 20 TOTAL_HITS_CACHE_REQ INT Y 21
CHARGE_DROP_PERCENT INT Y 22 TIME_ON_NOT_CHARGING LONG Y 23
TIME_RADIO_STATE_1 LONG Y 24 TIME_RADIO_STATE_2 LONG Y 25
TIME_RADIO_STATE_3 LONG Y 26 TIME_RADIO_STATE_4 LONG Y 27
TIME_RADIO_STATE_5 LONG Y 28 TIME_RADIO_STATE_6 LONG Y 29
TIME_RADIO_STATE_7 LONG Y 30 TIME_RADIO_STATE_8 LONG Y 31
TIME_RADIO_STATE_9 LONG Y 32 TIME_RADIO_STATE_10 LONG Y 33
TRANS_INTO_RADIO_STATE_1 INT Y 34 TRANS_INTO_RADIO_STATE_2 INT Y 35
TRANS_INTO_RADIO_STATE_3 INT Y 36 TRANS_INTO_RADIO_STATE_4 INT Y 37
TRANS_INTO_RADIO_STATE_5 INT Y 38 TRANS_INTO_RADIO_STATE_6 INT Y 39
TRANS_INTO_RADIO_STATE_7 INT Y 40 TRANS_INTO_RADIO_STATE_8 INT Y 41
TRANS_INTO_RADIO_STATE_9 INT Y 42 TRANS_INTO_RADIO_STATE_10 INT Y
43 RADIO_STATE_CHANGES_ACTUAL INT Y 44 RADIO_TIME_CONN_ACTUAL LONG
Y 45 RADIO_STATE_CHANGES_SAVED INT Y 46 RADIO_TIME_CONN_SAVED LONG
Y 47 SIM_RADIO_STATE_CHANGES_ACTUAL INT Y 48
SIM_RADIO_TIME_CONN_ACTUAL LONG Y 49 SIM_RADIO_STATE_CHANGES_SAVED
INT Y 50 SIM_RADIO_TIME_CONN_SAVED LONG Y 51 WCDMA_TRANS_INTO_DCH
INT Y 52 WCDMA_TRANS_INTO_FACH INT Y 53 WCDMA_TRANS_INTO_PCH INT Y
54 WCDMA_TRANS_INTO_IDLE INT Y 55 WCDMA_TIME_IN_DCH LONG Y 56
WCDMA_TIME_IN_FACH LONG Y 57 WCDMA_TIME_IN_PCH LONG Y 58
WCDMA_TIME_IN_IDLE LONG Y 59 NEW_SUBSCRIBER_COUNT INT Y 60
ACTIVE_SUBSCRIBER_COUNT INT Y 61 RECURRING_HASH LONG Y
[0634] FIG. 22 illustrates various example measurement points from
which a analysis core module such as, for example, analysis core
255a of FIG. 2E or CRSC analysis core 375a of FIG. 3E, can perform
measurements for modeling signals in the data network. Some
examples of the output metrics which can be adapted by the analysis
core module are listed in FIGS. 23A-23E.
[0635] As discussed above, in some embodiments the a analysis core
can make various calculations. For example, FIG. 24A graphically
illustrates an example of open channel bytes calculations.
[0636] In this example, with respect to the HTTPS traffic, the OC's
mock certificate is smaller than the certificate received from the
network, which would appear as negative savings. For HTTPS
handshakes, bytes-to-app are replaced with bytes-from-network. With
respect to from-app-bytes only, the OC receives the request
irrespective of network availability. Most often caused by network
unavailability. In cases when request does not go out to network
and is not served from cache, adjust OC-AT-ADJ to 0.
[0637] In this example, the difference between (adjusted)
Application (App) and Network Traffic is Saved Traffic (i.e.,
[OC-AT-ADJ]-[OC-NT]=[OC-ST]). The Saved Traffic plus the Total
Network Traffic is the total application traffic (i.e.,
[OC-ST]+[TNT]=[TAT]). The (adjusted) App Traffic divided by the
Total App Traffic is the Bytes Coverage (i.e.,
[OC-AT-ADJ]/[TAT]=BC.
[0638] In some embodiments, the open channel bytes calculation's
coverage can be affected by: [0639] Traffic channeled directly to
Network Interface instead of through: OC [0640] TCP ports
configured to bypass: IMAP, POP, 7TP [0641] OC client in failover
[0642] 3.sup.rd party client reconfiguring traffic flows (typically
tethering) [0643] Total Network Traffic recorded for incorrect
interfaces: Interfaces defined for TNT are configured manually. New
device models need to be verified. [0644] Temporal factors: Total
Network Traffic is recorded periodically, while OC Application
Traffic is recorded for each transaction. Disruptions in data
collection, such as device reboot may cause different cut-off for
these metrics. Network change notifications may also appear in a
middle of a longer transaction, making it unclear which network
interface was used. [0645] TCP/IP and UDP protocol overhead and TCP
retransmissions: measured for Total Network Traffic, but not
measured for OC Application Traffic.
[0646] FIGS. 24A-24J graphically illustrate various calculations of
example output metrics that can be used in embodiments of the
analysis core module.
[0647] FIG. 25 depicts an example diagram illustrating a general
architectural overview of a distributed Open Channel system
including the measurement points from which a analysis core module
can perform measurements for modeling signals in the data network.
FIGS. 26A-26N show additional examples of and/or alternative output
metrics that the analysis core module can adapt.
[0648] For example, FIGS. 26A-26C illustrate example Data Metrics.
FIGS. 26D-26F illustrate example Optimization Metrics. In some
embodiments, exception can exist for ISOC/ISOTC: Internal Signaling
Optimization formulas do not use simulated values in by protocol
calculations. FIG. 26G illustrates example Users Metrics. In some
embodiments, the user metrics can be used to provide the unique
number of users (e.g., as identified by 7TP address) or user
combinations within the time period of concern. Additionally, the
metrics may be useful to calculate metrics like bytes/connections
per user per day. FIG. 26H illustrates example Battery Metrics.
FIGS. 26I-26K illustrate example Signaling Metrics. For example, a
Signaling Overall metric can provide the number of state
transitions within the time period of concern, broken by the radio
state. Likewise, a Time Connected Overall can provide the time
connected within the time period of concern, broken by the radio
state. FIGS. 26L-26M illustrate example Dimensions Metrics. FIG.
26N illustrates example Optimization Metrics. FIG. 26N illustrates
example Optimization Metrics.
[0649] FIG. 27 shows a diagrammatic representation of a machine in
the example form of a computer system within which a set of
instructions, for causing the machine to perform any one or more of
the methodologies discussed herein, may be executed.
[0650] In alternative embodiments, the machine operates as a
standalone device or may be connected (e.g., networked) to other
machines. In a networked deployment, the machine may operate in the
capacity of a server or a client machine in a client-server network
environment, or as a peer machine in a peer-to-peer (or
distributed) network environment.
[0651] The machine may be a server computer, a client computer, a
personal computer (PC), a user device, a tablet PC, a laptop
computer, a set-top box (STB), a personal digital assistant (PDA),
a cellular telephone, an iPhone, an iPad, a Blackberry, a
processor, a telephone, a web appliance, a network router, switch
or bridge, a console, a hand-held console, a (hand-held) gaming
device, a music player, any portable, mobile, hand-held device, or
any machine capable of executing a set of instructions (sequential
or otherwise) that specify actions to be taken by that machine.
[0652] While the machine-readable medium or machine-readable
storage medium is shown in an exemplary embodiment to be a single
medium, the term "machine-readable medium" and "machine-readable
storage medium" should be taken to include a single medium or
multiple media (e.g., a centralized or distributed database and/or
associated caches and servers) that store the one or more sets of
instructions. The term "machine-readable medium" and
"machine-readable storage medium" shall also be taken to include
any medium that is capable of storing, encoding or carrying a set
of instructions for execution by the machine and that cause the
machine to perform any one or more of the methodologies of the
presently disclosed technique and innovation.
[0653] In general, the routines executed to implement the
embodiments of the disclosure may be implemented as part of an
operating system or a specific application, component, program,
object, module or sequence of instructions referred to as "computer
programs" The computer programs typically comprise one or more
instructions set at various times in various memory and storage
devices in a computer that, when read and executed by one or more
processing units or processors in a computer, cause the computer to
perform operations to execute elements involving the various
aspects of the disclosure.
[0654] Moreover, while embodiments have been described in the
context of fully functioning computers and computer systems, those
skilled in the art will appreciate that the various embodiments are
capable of being distributed as a program product in a variety of
forms, and that the disclosure applies equally regardless of the
particular type of machine or computer-readable media used to
actually effect the distribution.
[0655] Further examples of machine-readable storage media,
machine-readable media, or computer-readable (storage) media
include but are not limited to recordable type media such as
volatile and non-volatile memory devices, floppy and other
removable disks, hard disk drives, optical disks (e.g., Compact
Disk Read-Only Memory (CD ROMS), Digital Versatile Disks, (DVDs),
etc.), among others, and transmission type media such as digital
and analog communication links.
ADDITIONAL EMBODIMENTS
[0656] In some embodiments, a method of modeling signaling in a
mobile network is disclosed. The method includes: determining if
transactions initiated by mobile applications executing on a mobile
device in the mobile network cause network signaling requiring a
corresponding radio connection, wherein at least a portion of the
network signaling caused by the transactions is filtered by a
traffic optimization engine; and modeling the network signaling for
the mobile device based, at least in part, on the filtered network
signaling.
[0657] In some embodiments, the filtered network signaling does not
cause a corresponding radio connection.
[0658] In some embodiments, modeling the network signaling for the
mobile device further comprises calculating signaling efficiency
indicating a total number of the radio connections that are saved
as a result of the filtering.
[0659] In some embodiments, calculating the signaling efficiency
further comprises: accessing a radio log and a traffic activity log
associated with the mobile device; modeling a quantity of virtual
radio connections based on the radio log and the traffic activity
log, wherein the virtual radio connections indicate radio
connections that would occur but for said filtering; determining a
quantity of actual radio connections based on the radio log,
wherein the total number of the radio connections that are saved
comprises the difference between the quantity of virtual radio
connections and the quantity of actual radio connections.
[0660] In some embodiments, modeling the network signaling for the
mobile device further comprises calculating a time connected
efficiency indicating a total radio connection time saved as a
result of the filtering.
[0661] In some embodiments, calculating the time connected
efficiency further comprises: accessing a radio log and a traffic
activity log associated with the mobile device; modeling a virtual
radio time connected based on the radio log and the traffic
activity log, wherein the virtual radio time connected indicates an
amount of time that the mobile device radio would be active but for
said filtering; determining an actual radio time connected based on
the radio log, wherein the actual radio time connected indicates an
amount of time that the mobile device radio is active; wherein the
total radio connection time saved comprises the difference between
the virtual radio time connected and the actual radio time
connected.
[0662] In some embodiments, the methods further comprise tracking
the transactions initiated by the mobile applications executing on
the mobile device in the mobile network.
[0663] In some embodiments, the methods further comprise applying,
by the traffic optimization engine, a traffic optimization
technique to filter the network signaling such that at least the
portion of the network signaling is filtered.
[0664] In some embodiments, the methods further comprise accessing
traffic activity logs indicating traffic metrics measured at
multiple traffic measurement points in the mobile device, wherein
modeling the network signaling further comprises calculating a
connection status and a time connected interval based on the
traffic metrics.
[0665] In some embodiments, modeling the network signaling for the
mobile device further comprises attributing the network signaling
to individual applications of the mobile applications executing on
the mobile device.
[0666] In some embodiments, the methods further comprise accessing
a radio log and a traffic activity log associated with the mobile
device, wherein the radio log indicates a state of a mobile device
radio, wherein the traffic activity log indicates various traffic
metrics measured at multiple measurement points in the mobile
device; and maintaining the traffic activity log by calculating one
or more fields.
[0667] In some embodiments, modeling the network signaling based on
the one or more fields.
[0668] In some embodiments, maintaining the traffic activity log
comprises long polling.
[0669] In some embodiments, the one or more fields are divided into
connection flag fields and time connected count fields.
[0670] In some embodiments, the one or more fields are categorized
into one or more of the following categories: actual, simulated,
actual simulated, virtual simulated, actual simulated per
application, and virtual simulated per application.
[0671] In some embodiments, the traffic optimization engine
comprises one or more elements of a distributed caching and proxy
system.
[0672] In some embodiments, the distributed caching and proxy
system includes a proxy client and a proxy server.
[0673] In some embodiments, the filtered radio connections are
cached locally by the proxy client.
[0674] In some embodiments, a method of modeling network signaling
in a mobile network is disclosed. The method comprises: accessing a
radio log associated with a mobile device operating in the mobile
network, the radio log indicating a state of a mobile device radio;
accessing a traffic activity log associated with the mobile device,
the traffic activity log indicating various traffic metrics
measured at multiple measurement points in the mobile device;
calculating one or more fields based on one or more of the radio
log and the traffic activity log; and modeling the network
signaling for the mobile device based on the one or more
fields.
[0675] In some embodiments, the method further comprises
determining if transactions initiated by mobile applications
executing on the mobile device in the mobile network cause network
signaling requiring a corresponding radio connection on the mobile
device, wherein at least a portion of the network signaling caused
by the transactions is filtered by a traffic optimization
engine.
[0676] In some embodiments, the filtered network signaling does not
cause a corresponding radio connection on the mobile device and the
unfiltered network signaling does cause corresponding radio
connection on the mobile device.
[0677] In some embodiments, modeling the network signaling further
comprises calculating a connection status and a time connected
interval based, at least in part, on the one or more calculated
fields.
[0678] In some embodiments, modeling the network signaling for the
mobile device further comprises calculating signaling efficiency
indicating a total number of the radio connections that are saved
as a result of the filtering.
[0679] In some embodiments, calculating the signaling efficiency
further comprises: accessing a radio log and a traffic activity log
associated with the mobile device; modeling a quantity of virtual
radio connections based on the radio log and the traffic activity
log, wherein the virtual radio connections indicate radio
connections that would occur but for said filtering; determining a
quantity of actual radio connections based on the radio log,
wherein the total number of the radio connections comprises the
difference between the quantity of virtual radio connections and
the quantity of actual radio connections.
[0680] In some embodiments, modeling the network signaling for the
mobile device further comprises calculating a time connected
efficiency indicating a total radio connection time saved as a
result of the filtering.
[0681] In some embodiments, calculating the time connected
efficiency further comprises: accessing a radio log and a traffic
activity log associated with the mobile device; modeling a virtual
radio time connected based on the radio log and the traffic
activity log, wherein the virtual radio time connected indicates an
amount of time that the mobile device radio would be active but for
said filtering; determining an actual radio time connected based on
the radio log, wherein the actual radio time connected indicates an
amount of time that the mobile device radio is active; wherein the
total radio connection time saved comprises the difference between
the virtual radio time connected and the actual radio time
connected.
[0682] In some embodiments, the methods further comprise
maintaining the traffic activity log by tracking transactions and
measuring the various traffic metrics at the multiple measurement
points in the mobile device.
[0683] In some embodiments, the one or more fields are divided into
connection flag fields and time connected count fields.
[0684] In some embodiments, the one or more fields are categorized
into one or more of the following categories: actual, simulated,
actual simulated, virtual simulated, actual simulated per
application, and virtual simulated per application.
[0685] In some embodiments, a mobile device is disclosed. The
mobile device comprise a radio; a processor; and a memory storing
instruction, wherein the instructions, when executed by the
processor, causes the mobile device to: access a radio log
associated with a mobile device operating in the mobile network,
the radio log indicating a state of a mobile device radio; access a
traffic activity log associated with the mobile device, the traffic
activity log indicating various traffic metrics measured at
multiple measurement points in the mobile device; calculate one or
more fields based on one or more of the radio log and the traffic
activity log; and model the network signaling for the mobile device
based on the one or more fields.
[0686] In some embodiments, wherein the instructions, when executed
by the processor, further causes the mobile device to: determine if
transactions initiated by mobile applications executing on the
mobile device in the mobile network cause network signaling
requiring a corresponding radio connection on the mobile device,
wherein at least a portion of the network signaling caused by the
transactions is filtered by a traffic optimization engine, wherein
the filtered network signaling does not cause a corresponding radio
connection on the mobile device and the unfiltered network
signaling does cause corresponding radio connection on the mobile
device.
[0687] In some embodiments, the mobile further comprises a traffic
optimization engine comprising one or more elements of a
distributed caching and proxy system.
[0688] In some embodiments, the distributed caching and proxy
system includes a proxy client and a proxy server, and wherein the
filtered radio connections are cached locally by the proxy
client.
[0689] In some embodiments, the instructions, when executed by the
processor, further causes the mobile device to: track transactions
initiated by mobile applications executing on the mobile device in
the mobile network; measure the various traffic metrics at the
multiple measurement points in the mobile device; and maintain the
traffic activity log based on the measurements.
[0690] In some embodiments, to model the network signaling for the
mobile device, the instructions, when executed by the processor,
further causes the mobile device to calculate signaling efficiency
indicating a total number of the radio connections that are saved
as a result of the filtering.
[0691] In some embodiments, to calculate the signaling efficiency,
the instructions, when executed by the processor, further causes
the mobile device to: access a radio log and a traffic activity log
associated with the mobile device; model a quantity of virtual
radio connections based on the radio log and the traffic activity
log, wherein the virtual radio connections indicate radio
connections that would occur but for said filtering; determine a
quantity of actual radio connections based on the radio log,
wherein the total number of the radio connections comprises the
difference between the quantity of virtual radio connections and
the quantity of actual radio connections.
[0692] In some embodiments, to model the network signaling for the
mobile device, the instructions, when executed by the processor,
further causes the mobile device to calculate a time connected
efficiency indicating a total radio connection time saved as a
result of the filtering.
[0693] In some embodiments, to calculate the time connected
efficiency, the instructions, when executed by the processor,
further causes the mobile device to: access a radio log and a
traffic activity log associated with the mobile device; model a
virtual radio time connected based on the radio log and the traffic
activity log, wherein the virtual radio time connected indicates an
amount of time that the mobile device radio would be active but for
said filtering; determine an actual radio time connected based on
the radio log, wherein the actual radio time connected indicates an
amount of time that the mobile device radio is active; wherein the
total radio connection time saved comprises the difference between
the virtual radio time connected and the actual radio time
connected.
[0694] In some embodiments, a computer-readable storage medium
storing instructions to be implemented by a mobile device having a
processor is the discloses. The instructions, when executed by the
processor, causes the mobile device to: determine if transactions
initiated by mobile applications executing on the mobile device in
a mobile network cause network signaling requiring a corresponding
radio connection, wherein at least a portion of the network
signaling caused by the transactions is filtered by a traffic
optimization engine, wherein the filtered network signaling does
not cause a corresponding radio connection; and modeling the
network signaling for the mobile device based, at least in part, on
the filtered network signaling.
[0695] In some embodiments, modeling the network signaling for the
mobile device further comprises calculating signaling efficiency
indicating a total number of the radio connections that are saved
as a result of the filtering.
[0696] In some embodiments, modeling the network signaling for the
mobile device further comprises calculating a time connected
efficiency indicating a total radio connection time saved as a
result of the filtering.
[0697] In some embodiments, the instructions, when executed by the
processor, further cause the processor to: access a radio log and a
traffic activity log associated with the mobile device, wherein the
radio log indicates a state of a mobile device radio, wherein the
traffic activity log indicates various traffic metrics measured at
multiple measurement points in the mobile device; and maintain the
traffic activity log by calculating one or more fields.
[0698] In some embodiments, modeling the network signaling is based
on the one or more fields.
[0699] Unless the context clearly requires otherwise, throughout
the description and the claims, the words "comprise," "comprising,"
and the like are to be construed in an inclusive sense, as opposed
to an exclusive or exhaustive sense; that is to say, in the sense
of "including, but not limited to." As used herein, the terms
"connected," "coupled," or any variant thereof, means any
connection or coupling, either direct or indirect, between two or
more elements; the coupling of connection between the elements can
be physical, logical, or a combination thereof. Additionally, the
words "herein," "above," "below," and words of similar import, when
used in this application, shall refer to this application as a
whole and not to any particular portions of this application. Where
the context permits, words in the above Detailed Description using
the singular or plural number may also include the plural or
singular number respectively. The word "or," in reference to a list
of two or more items, covers all of the following interpretations
of the word: any of the items in the list, all of the items in the
list, and any combination of the items in the list.
[0700] The above detailed description of embodiments of the
disclosure is not intended to be exhaustive or to limit the
teachings to the precise form disclosed above. While specific
embodiments of, and examples for, the disclosure are described
above for illustrative purposes, various equivalent modifications
are possible within the scope of the disclosure, as those skilled
in the relevant art will recognize. For example, while processes or
blocks are presented in a given order, alternative embodiments may
perform routines having steps, or employ systems having blocks, in
a different order, and some processes or blocks may be deleted,
moved, added, subdivided, combined, and/or modified to provide
alternative or sub-combinations. Each of these processes or blocks
may be implemented in a variety of different ways. Also, while
processes or blocks are at times shown as being performed in
series, these processes or blocks may instead be performed in
parallel, or may be performed at different times. Further any
specific numbers noted herein are only examples: alternative
implementations may employ differing values or ranges.
[0701] The teachings of the disclosure provided herein can be
applied to other systems, not necessarily the system described
above. The elements and acts of the various embodiments described
above can be combined to provide further embodiments.
[0702] Any patents and applications and other references noted
above, including any that may be listed in accompanying filing
papers, are incorporated herein by reference. Aspects of the
disclosure can be modified, if necessary, to employ the systems,
functions, and concepts of the various references described above
to provide yet further embodiments of the disclosure.
[0703] These and other changes can be made to the disclosure in
light of the above Detailed Description. While the above
description describes certain embodiments of the disclosure, and
describes the best mode contemplated, no matter how detailed the
above appears in text, the teachings can be practiced in many ways.
Details of the system may vary considerably in its implementation
details, while still being encompassed by the subject matter
disclosed herein. As noted above, particular terminology used when
describing certain features or aspects of the disclosure should not
be taken to imply that the terminology is being redefined herein to
be restricted to any specific characteristics, features, or aspects
of the disclosure with which that terminology is associated. In
general, the terms used in the following claims should not be
construed to limit the disclosure to the specific embodiments
disclosed in the specification, unless the above Detailed
Description section explicitly defines such terms. Accordingly, the
actual scope of the disclosure encompasses not only the disclosed
embodiments, but also all equivalent ways of practicing or
implementing the disclosure under the claims.
[0704] While certain aspects of the disclosure are presented below
in certain claim forms, the inventors contemplate the various
aspects of the disclosure in any number of claim forms. For
example, while only one aspect of the disclosure is recited as a
means-plus-function claim under 35 U.S.C. .sctn. 112, 16, other
aspects may likewise be embodied as a means-plus-function claim, or
in other forms, such as being embodied in a computer-readable
medium. (Any claims intended to be treated under 35 U.S.C. .sctn.
112, 16 will begin with the words "means for.") Accordingly, the
applicant reserves the right to add additional claims after filing
the application to pursue such additional claim forms for other
aspects of the disclosure.
* * * * *
References