U.S. patent application number 15/702003 was filed with the patent office on 2018-02-08 for automatic content replication.
The applicant listed for this patent is Microsoft Technology Licensing, LLC. Invention is credited to Bippen Bisht, Leyu Feng, David C. James, Prasanna K. Jayapal, Brandon M. Waterloo.
Application Number | 20180039684 15/702003 |
Document ID | / |
Family ID | 53544997 |
Filed Date | 2018-02-08 |
United States Patent
Application |
20180039684 |
Kind Code |
A1 |
Jayapal; Prasanna K. ; et
al. |
February 8, 2018 |
AUTOMATIC CONTENT REPLICATION
Abstract
Content can be replicated automatically to facilitate
distribution of the content to one or more devices. Determinations
can be made automatically regarding where to replicate data, how to
replicate data, and when to replicate data based on a variety of
collected data with respect to devices, content servers, content
sources, and content. More particularly, one or more content
servers can be identified as targets for content replication and a
protocol can be determined to replicate content from at least one
source to the one or more content servers identified. Subsequently,
replication can be initiated to the one or more content servers
with the corresponding protocol at a determined time. Further,
similar mechanisms can be employed to enable automatic
determination of how and when to distribute or replicate content
from one or more content servers to one or more target devices.
Inventors: |
Jayapal; Prasanna K.;
(Bothell, WA) ; James; David C.; (Snohomish,
WA) ; Feng; Leyu; (Redmond, WA) ; Bisht;
Bippen; (Redmond, WA) ; Waterloo; Brandon M.;
(Redmond, WA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Microsoft Technology Licensing, LLC |
Redmond |
WA |
US |
|
|
Family ID: |
53544997 |
Appl. No.: |
15/702003 |
Filed: |
September 12, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
14158763 |
Jan 17, 2014 |
9792339 |
|
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15702003 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 16/27 20190101 |
International
Class: |
G06F 17/30 20060101
G06F017/30 |
Claims
1. A method performed by a system comprising at least one processor
coupled to memory storing machine-executable instructions, which,
when executed, control the system to perform acts comprising:
receiving identification of content and a set of target devices
prior to distribution of the content to the set of target devices;
selecting one or more content servers to target automatically, from
one or more available content servers, in response to the
identification of the content and set of target devices, based on
configuration of the one or more available content servers and
network latency; and initiating automatic replication to the one or
more selected content servers.
2. The method of claim 1 further comprises selecting the one or
more content servers based on the content.
3. The method of claim 2 further comprises selecting the one or
more content servers based the set of target devices.
4. The method of claim 1 further comprises selecting the one or
more content servers based on one or more of distance between a
content source and the one or more available content servers or
distance between one or more available content servers and the set
of target devices.
5. The method of claim 1 further comprises selecting the one or
more content servers based on a roaming pattern of at least one
device in the set of target devices.
6. The method of claim 1 further comprises selecting the one or
more content servers based on one or more user specified
constraints.
7. The method of claim 1 further comprises automatically
determining a protocol to replicate content from a source to the
one or more content servers selected.
8. The method of claim 7 further comprises determining the protocol
based on at least one of number of content servers selected,
location of the content servers, or quality of a communication link
between a content source and the one or more content servers.
9. The method of claim 7 further comprises initiating replication
of the content to the one or more content servers with the protocol
determined for the one or more content servers automatically.
10. The method of claim 9 further comprises determining when to
initiate replication of the content based one or more of a
deadline, past performance, or content priority.
11. The method of claim 1 further comprises automatically
determining a protocol and time to distribute the content from the
one or more content servers to the set of target devices.
12. A system, comprising: a processor coupled to a memory, the
processor configured to execute computer-executable instructions
stored in the memory that when executed perform acts comprising:
analyzing content distribution system resources including devices
and content servers, and network latency; and identifying one or
more content servers to target automatically for duplicate content
to enable efficient distribution of content to a set of target
devices based on results of analysis of the content distribution
system resources and network latency.
13. The system of claim 12 further comprises identifying one or
more protocols for content replication for the one or more content
servers identified automatically based on at least one of number of
the one or more content servers identified, location of the one or
more content servers relative to each other, or quality of a
communication link between a content source and the one or more
content servers.
14. The system of claim 13 further comprises initiating replication
of content with the one or more protocols on the one or more
content servers identified based on at least one of deadline, past
performance, or roaming pattern of one or more target devices of
the set of target devices.
15. The system of claim 12, further comprises assigning to
available content servers at least one of an initial weight based
on content server configuration.
16. The system of claim 12 further comprises assigning to available
content servers a specific weight based on the content to be
distributed and the set of target devices.
17. A computer-readable storage medium having instructions stored
thereon that enable at least one processor to perform a content
replication method upon execution of the instructions, the method
comprising: receiving identification of content and a set of target
devices, specified by a user, prior to distribution of the content
to the set of target devices; identifying one or more content
servers to target for replicated content automatically, in response
to identification of the content and the set of target devices,
based on network latency between content sources and servers;
determining a protocol to replicate the content from one or more
content sources to the one or more content servers; and determining
when to initiate content replication to the one or more content
servers in accordance with the protocol; and initiating content
replication from the one or more content sources to the one or more
the one or more content servers identified with the protocol
determined at a time determined.
18. The computer-readable storage medium of claim 17, the method
further comprises identifying the one or more content servers to
target automatically based on at least one of location of one or
more available content servers, configuration of one or more
available content servers, the content, or target devices.
19. The computer-readable storage medium of claim 17, the method
further comprises determining the protocol automatically based on
at least one of number of the one or more content servers
identified, location of the one or more content servers identified,
or quality of a communication link between the content source and
the one or more content servers.
20. The computer-readable storage medium of claim 17, the method
further comprises determining when to initiate content replication
automatically based on at least one of a deadline, past
performance, or content priority.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application is a continuation of U.S. application Ser.
No. 14/158,763 filed Jan. 17, 2014, the entirety of which is
incorporated herein by reference.
BACKGROUND
[0002] A content distribution system comprises a collection of
network-connected content servers arranged to facilitate delivery
of content to end-users by way of end-user devices. Central to
content distribution is content replication, which pertains to
duplicating content across multiple content servers. Content can
then be delivered to end-user devices in a reliable and timely
manner from the content servers.
[0003] Content distribution systems are typically managed by
information technology (IT) administrators. Conventionally, an IT
administrator selects at least one content server and pushes the
content to the at least one content server. Subsequently, the IT
administrator initiates download of the content by target devices
from the one or more content servers.
SUMMARY
[0004] The following presents a simplified summary in order to
provide a basic understanding of some aspects of the disclosed
subject matter. This summary is not an extensive overview. It is
not intended to identify key/critical elements or to delineate the
scope of the claimed subject matter. Its sole purpose is to present
some concepts in a simplified form as a prelude to the more
detailed description that is presented later.
[0005] Briefly described, the subject disclosure pertains to
automatic content replication. Determinations can be made
automatically with respect to where, how, and when to replicate
content to enable efficient distribution of content to a set of
target devices. The determinations can be based on a variety of
factors associated with content servers, target devices, content
sources, and content. Based on acquired data, one or more content
servers can be targeted for replicate content, a protocol can be
determined for use with respect to replicating content to the one
or more content servers, and a time determined for initiating
replication. Subsequently, content can be replicated to the one or
more content servers targeted with the protocol at the determined
time. In accordance with one aspect, a variety of weights capturing
replication relevant data can be computed and assigned to content
servers and distances related to content servers calculated to
facilitate determinations regarding where, how, and when to
replicate data. Similar mechanisms can also be employed
automatically to determine at least how and when to replicate
content from one or more content servers to one or more target
devices.
[0006] To the accomplishment of the foregoing and related ends,
certain illustrative aspects of the claimed subject matter are
described herein in connection with the following description and
the annexed drawings. These aspects are indicative of various ways
in which the subject matter may be practiced, all of which are
intended to be within the scope of the claimed subject matter.
Other advantages and novel features may become apparent from the
following detailed description when considered in conjunction with
the drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] FIG. 1 is a block diagram of a content replication
system.
[0008] FIG. 2 is a block diagram of a representative analysis
component.
[0009] FIG. 3 is a block diagram of a representative weight
component.
[0010] FIG. 4 is a block diagram of a representative distance
component.
[0011] FIG. 5 is a flow chart diagram of a method of content
replication.
[0012] FIG. 6 is a flow chart diagram of a method of content
replication.
[0013] FIG. 7 is a flow chart diagram of relevant data
collection.
[0014] FIG. 8 is a flow chart diagram of a method of specific
weight computation.
[0015] FIG. 9 is a flow chart diagram of a method of distributing
content to target devices.
[0016] FIG. 10 is a flow chart diagram of a change response
method.
[0017] FIG. 11 is a flow chart diagram of a method determining
specific weight for content servers.
[0018] FIG. 12 is a flow chart diagram of method of content
replication.
[0019] FIG. 13 is a schematic block diagram illustrating a suitable
operating environment for aspects of the subject disclosure.
DETAILED DESCRIPTION
[0020] Conventionally, content distribution systems employ two
manual processing steps. First, an information technology (IT)
administrator pushes content to a content server. Second, the IT
administrator initiates download of the content from the content
server by devices. In addition, planning and staging is difficult,
especially in large-scale enterprise systems and in cases where
devices roam across locations, resulting in inefficiencies.
[0021] Details below generally pertain to automatic content
replication. Determinations are made automatically regarding where
to replicate data, how to replicate data, and when to replicate
data in order to provision content efficiently to a target set of
devices. More specifically, one or more content servers can be
targeted as staging locations for replicated content based on a
variety of data collected with respect to devices, content servers,
content sources, content priority, and the rules defined by the IT
administrator. One or more protocols can be determined with respect
to provisioning content to the one or more content servers, for
example, based on the number of target content servers, location,
and the quality of communication links between a content source and
content servers. Further, a determination is made as to when to
initiate content replication based on factors such as the priority
of the content, deadline, past performance, and the protocol
chosen. Additionally, similar mechanisms can be employed to
automatically determine how and when to distribute or replicate
content from one or more content servers to one or more target
devices. As a result, IT administrators can merely identify content
and target devices and are relieved of extensive planning, which is
typically inadequate or inaccurate, as well as manual processing
steps. Moreover, such automatic replication can be configured to
enable target devices to acquire content as quickly and efficiently
as possible.
[0022] Various aspects of the subject disclosure are now described
in more detail with reference to the annexed drawings, wherein like
numerals generally refer to like or corresponding elements
throughout. It should be understood, however, that the drawings and
detailed description relating thereto are not intended to limit the
claimed subject matter to the particular form disclosed. Rather,
the intention is to cover all modifications, equivalents, and
alternatives falling within the spirit and scope of the claimed
subject matter.
[0023] Referring initially to FIG. 1, a content replication system
100 is illustrated. The content replication system 100 is
configured to automatically replicate data to one or more target
devices quickly and efficiently. Herein, content refers more
specifically to electronic content comprising data that can be
disseminated across a network, such as the Internet,
electronically. For example, content can comprise, among other
things, software, and digital media including images, audio, and
video. A content server is configured to store content and serve,
replicate, or otherwise make data available to devices, which are
computer devices, or simply computers, including desktops, laptops,
tablets, and mobile devices (e.g., smart phones), among other
things. A content server can also be said to act as a temporary
stage for content prior to distribution to devices, and thus, to
stage content means to save the content for later distribution. A
content server can also be referred to as a distribution point,
edge node, or staging server. Further, a content server can be an
on-premises server, a cloud storage location, a server located in a
datacenter, a personal computer, or other variations.
[0024] The content replication system 100 includes analysis
component 110, repository 120, target component 130, protocol
component 140, and trigger component 150. In brief, the analysis
component 110 is configured to analyze the infrastructure and
resources of a content distribution system, and store results in
the repository 120, for use in automatically determining where,
how, and when to replicate content. The target component 130 is
configured to identify one or more content servers to target for
replicate data to enable the data to subsequently be provided to
one or more target devices. The protocol component 140 is
configured to determine a protocol to utilize in conjunction with
replicating content to one or more identified content servers, and
the trigger component 150 is configured to initiate replication of
content to the one or more identified servers with one or more
corresponding protocols at a determined time. The protocol
component 140 and trigger component 150 can also be utilized in a
similar manner to determine how and when to serve content to target
devices. Each component will now be described in further
detail.
[0025] The analysis component 110 is configured to acquire
information regarding devices, content servers, content sources,
and content, among other things. For instance, the analysis
component 110 can keep track of all devices in an organization and
information about and concerning devices including but not limited
to IP (Internet Protocol) address and network boundaries, subnets,
or active directory sites to which devices belong. These data
points contribute to deciding which boundary group a device belongs
to if not otherwise known, wherein a boundary group is a virtual
demarcation that aids grouping devices and content servers that are
in close proximity. The analysis component 110 can also acquire
information about all available content servers such as their
locations, configuration (e.g., processor, memory, software . . .
), network configurations, boundary details, bandwidth throttling
constraints, and sites to which they are assigned. Location and
configuration of a content source can also be determined by the
analysis component 110. Further, content itself can be analyzed to
determine content size, execution environment (e.g., x86), and
priority, among other things. After acquisition, the data or
information can be saved to the repository 120 in a manner
accessible for use by other components.
[0026] Turning attention to FIG. 2, a representative analysis
component 110 is depicted in further detail. In addition to
identifying and recording information, the analysis component can
process data to produce useful results. As shown, the analysis
component 110 includes weight component 210 and distance component
220. The weight component 210 is configured to compute, calculate,
or otherwise determine a weight from other information. In
accordance with one embodiment, the weight component 210 can
compute weights for content servers that capture various aspects of
content servers. The distance component 220 is configured to
compute, calculate, or otherwise determine distances between
various elements of a content distribution system, which allow
determinations regarding proximity.
[0027] FIG. 3 illustrates representative weight component 210 in
further detail. The weight component 210 includes initial weight
component 310 and specific weight component 320. The initial weight
component 310 is configured to compute an initial weight without
regard to specifics, for instance regarding content and targeted
devices. For example, the initial weight component 310 can compute
a value representative of efficiency and performance with respect
to storing content as well as provisioning data to devices. In this
case, a content server configuration including processor, memory,
and storage, for instance can be utilized to produce the weight.
Furthermore, the type of the content server such as on premise, in
the cloud, or at a third-party location can be considered.
[0028] The specific weight component 320 generates weights for
content servers specific to content and targeted devices. In
accordance with one embodiment, a specific weight can be generated
based on, or as a function of, an initial weight. Further, a
specific weight can result from updating or otherwise modifying an
initial weight to reflect specifics. For example, content servers
that include space to store the content can be weighted more
favorably that those that cannot support the size of the content.
Additionally, content servers that reach more devices that provide
an execution environment used by the content can be weighted more
favorably than those that include smaller numbers of such devices.
Further, the content server weights can be adjusted to reflect a
number of target devices reachable by a content server such that
those content servers that reach more target devices than others
are weighted more favorably. Further, weights can be adjusted as a
function of device roaming. For instance, where based on historical
or other information it can be determined or inferred that a
specific target devices roams across different locations, content
servers that can reach such a device or are within the roaming
pattern can be weighted more favorably than those outside the
roaming pattern. Specific weights can also reflect additional or
custom criteria specified by an administrator to reflect
administrator knowledge or preferences, or customer limitations,
for example. For example, if for some reason one content server is
preferred over another that server can be weighted to reflect the
preference.
[0029] Specific weights can also be computed based on content
priority. At any given time there could be different content
flowing through a system. High priority content can be given
preference over low priority content. In other words, content
priority is similar to a weight for content. Priority can be
automatically computed or an administrator can define priority of
content. By way of example, security patches are usually defined as
high priority content. Integration of priority with specific
weights enables production of weights at least specific to content
and content server pairs.
[0030] FIG. 4 shows a representative distance component 220 in
further detail. Again, the distance component 220 is configured to
compute, calculate, or otherwise determine distances. Distance
includes but is not limited physical distance, number of network
hops between a source and a destination, and latency. As depicted,
the distance component 220 includes source distance component 410,
device distance component 420, and content server distance
component. The source distance component 410 is configured to
determine the distance from source content to one or more content
servers. In other words, distance of source content to a potential
staging location for a replica on a content server is computed,
calculated, or otherwise determined. The distance between a source
and content server can be significant in selecting a content server
for data replication, since it is likely that it is faster and more
efficient to replicate data from a source to a content server that
is closer to the source rather than farther from the source. The
device distance component 420 is configured to determine the
distance between a content server and one or more devices that are
able to acquire content from the server. Here, the distance of a
target devices to a content server may be noteworthy in selecting a
content server, as it may be more efficient to target a content
server that is closer to target devices rather than farther away
from target devices. The content server distance component 430 is
configured to determine the distance between content servers.
Content servers can also function as a source for other content
servers. Accordingly, the distance between content servers can be
significant in determining whether to replicate content from one
content server to another content server. Here, it may be more
efficient to replicate content between content servers that are
closer in distance as opposed to farther away.
[0031] With respect to the analysis component 110, note that device
association can optionally be employed as an indirect way to
compute weights as well as content paths. For example, content is
targeted to users, and users can have multiple devices.
Accordingly, a content path can be calculated from a source to
multiple user devices. However, a higher weight can be given to
devices that are frequently used by a user. Stated differently,
higher preference is given to user's primary device (e.g., most
frequently used) over less frequently used devices.
[0032] Returning to FIG. 1, the repository 120 is a place where
data can be stored and maintained. By way of example, the
repository can correspond to a one or more files or databases.
Moreover, the repository 120 and store a plurality of data or
information associated with content distribution and more
particularly content replication. For instance, the repository can
store data collected and generated by the analysis component 110
and make this data available for use by other components. As
another non-limiting example, the repository 120 can store
additional or custom rules, criteria, or limitations input by an IT
administrator or other person. Furthermore, in one instance the
repository can be local to other components as shown. However, the
repository can also be located remote to other components but
accessible by the components.
[0033] The target component 130 is configured to identify one or
more content servers as targets for replicated content based on a
variety of factors. Furthermore, selection of content servers can
be performed automatically without human interaction. Some factors
considered by the target component 130 include content server
configuration (e.g., hardware, software), location, distance
relative to a content server, content, target devices, and
device-roaming pattern. As a simple example, if a number of target
devices are located in a branch office and there is a content
server in the branch office, the content server can be identified
as a target for replicate data to enable content to be provided to
the devices in the branch office. Furthermore, the target component
130 can be configured to minimize network traffic, network
bandwidth consumption, or distance (e.g., physical, network hops,
latency), as much possible in selecting one or more content servers
to enable content to be distributed to target devices quickly and
efficiently.
[0034] In accordance with one implementation, weights can be
assigned to content servers that capture various factors related to
efficiently identifying content servers. In this scenario, the
target component 130 can utilize previously calculated weights
(e.g., by analysis component 110), initiate weight computation, or
determine weights itself and utilize the weights to identify target
content servers. By way of example, and not limitation, given
content and a set of target devices, the target component 130 can
employ initial or standard weights capturing content server
configuration (e.g., storage space, availability, I/O efficiency),
network bandwidth, and number of devices served, for example to
identify an initial list of one or more content servers.
Subsequently, specific weights associated with the content and
target devices can be employed to narrow the list. For example,
content servers can be weighted based on ability to store the
content (e.g., available storage space) and the number of target
devices that can be served by the content server.
[0035] As an example, consider a case where there are a set of
devices "D" in a boundary group (e.g., a virtual demarcation that
aids identifying devices and content servers in close proximity)
"B" for which content "C" is targeted. The target component 130 can
seek locate a content server "S" in the same boundary group as the
set of devices "D" to minimize the distance between a content
server and target devices. If there are multiple content servers in
the boundary group, the best suitable content server for this
scenario can be identified for example based on availability
storage space, efficiency, network traffic, and load on the server,
among other things. If no content servers are present in a boundary
group comprising devices, the target component can locate the
nearest remote content server that can efficiently serve devices in
the boundary group.
[0036] The protocol component 140 is configured to determine a
protocol to replicate content to identified content targets
automatically. One aspect of determining the protocol comprises
selecting one or more of pull, push, or broadcast protocols to
employ. The push protocol pertains to pushing content from a source
to a destination. In accordance with one aspect, content stored at
one location (e.g., original/master content source) and be pushed
to a set of content servers that are centrally located and can be
accessed by various content servers and devices from different
boundary groups. The pull protocol concerns pulling content from a
source by a destination. In one instance, a specific instruction
can be sent to content servers with details indicating where to
pull the content. Further, primary and secondary locations for
content can be provided such that if content servers cannot pull
content from the primary location the secondary can be employed as
a fallback. Broadcast protocol establishes a session which content
servers can participate to acquire the content. Similar to the pull
protocol, content servers can be notified with specific
instructions that identify who will initiate a session and any
fallback sessions.
[0037] The protocol determination can be based on a number of
factors. One factor is which protocols are supported by content
targets. If a content server supports a single protocol such as
push, that is the protocol selected. If a content server supports
more than one protocol, other factors can be considered including
the number of content servers, location, and the quality of
communication links (e.g., reliability, bandwidth, speed . . . )
between a content source and one or more content servers. For
example, if there is a single content server that is to be provided
content the content can be pushed to the content server. As another
example, if there are multiple content servers in substantially the
same location close to a source, broadcast can be selected. In yet
another example, if there are multiple content servers in
substantially the same location with a slow or unreliable
communication link, the pull protocol can be selected to allow the
content servers to acquire the content from the source.
[0038] The protocol component 140 can also handle arbitrarily
complex scenarios. For instance, the source location can be
determined based on a variety of factors including network
bandwidth, speed, and traffic. Furthermore, content servers can be
targets for replicated content and subsequently content sources.
Still further, a combination of protocols can be employed for
identified content servers. By way of example and not limitation,
content can be pushed from an original content source to a few
content servers and for the remaining content servers identified to
stage content, a notification can be sent notifying them to either
pull content down from other content servers or participate in a
broadcast session to acquire the content.
[0039] The trigger component 150 is configured to initiate content
replication to one or more content servers identified by the target
component 130 by way of one or more protocols determined by the
protocol component 140. Moreover, the trigger component 150 is
configured to determine when to initiate content replication based
on several factors including a deadline, past performance, and a
roaming pattern of one or more devices among other things. When a
content replication is initiated can also be a function of whether
the content is mandatory or optional for devices. Where the content
is mandatory that means all target devices need to receive the
content and often there can be a deadline associated with content
delivery. In this case, path from a content source to a content
server and from the content server to the device can be considered
in making the determination of when to initiate replication to
comply with the deadline. Further, past performance can be
considered as well as roaming patterns since it may take additional
time for a device outside a network or roams to different
locations. In an optional scenario, simply needs to be provided to
the content server. Accordingly, the path or distance between the
content source and one or more content servers can be considered in
the determination. In accordance with one implementation, weights
that capture pertinent information related to content replication
can be determined and assigned to facilitate determining when to
initiate replication.
[0040] Initiating content replication can vary based on protocol or
in other words how content is to be replicated. For example, in the
context of pull protocol, target devices can be notified that
content is available with details regarding where the content is
located. As per, push the content can be pushed after first
notifying the device that content is incoming or without
notification. With respect to broadcast, devices can be notified
that a session is being established by a particular entity with an
invitation to join the session to acquire content. Furthermore, a
replication order may be established. Consequently, initiation of
content replication may be performed in multiple phases or steps to
implement the order.
[0041] The target component 130, the protocol component 140, and
the trigger component 150 can be configured to support
customization. For example, additional rules, constraints, or
limitations can be specified, for example by an IT administrator,
that affect which content servers are targeted. Similarly, existing
rules or the like can be customized, which likewise affect which
content servers are selected. As another example, a content path
for content can be overridden, and one could specify what protocol
a system should use to distribute the content. As yet another
example, a determined time to initiate replication can be
overridden and substituted with a specified time. Support for
customization enables IT administrators to inject their knowledge
into the automatic system as well as requirements of software
customers.
[0042] Although described extensively with respect to replicating
data with respect to content servers, it is be appreciated that
similar mechanisms can be utilized with respect to automatically
determining at least how and when content is to be provided or
replicated from a content server to a target device. In particular,
a two-stage process can be performed, wherein first, a
determination is made regarding replication of data to content
servers and second, a determination is made with respect to
replication of data from content servers to target devices.
However, the determinations need not be independent from one
another, but rather in one embodiment, determinations can be made
in conjunction with each other.
[0043] The aforementioned systems, architectures, environments, and
the like have been described with respect to interaction between
several components. It should be appreciated that such systems and
components can include those components or sub-components specified
therein, some of the specified components or sub-components, and/or
additional components. Sub-components could also be implemented as
components communicatively coupled to other components rather than
included within parent components. Further yet, one or more
components and/or sub-components may be combined into a single
component to provide aggregate functionality. Communication between
systems, components and/or sub-components can be accomplished in
accordance with either a push and/or pull model. The components may
also interact with one or more other components not specifically
described herein for the sake of brevity, but known by those of
skill in the art.
[0044] Furthermore, various portions of the disclosed systems above
and methods below can include or employ of artificial intelligence,
machine learning, or knowledge or rule-based components,
sub-components, processes, means, methodologies, or mechanisms
(e.g., support vector machines, neural networks, expert systems,
Bayesian belief networks, fuzzy logic, data fusion engines,
classifiers . . . ). Such components, inter alia, can automate
certain mechanisms or processes performed thereby to make portions
of the systems and methods more adaptive as well as efficient and
intelligent. By way of example, and not limitation, the content
replication system 100 and various components thereof may include
such mechanisms to facilitate efficient and adaptive replication.
For instance, the content replication system 100 can be implemented
as a rules engine that takes environmental and other variables into
account and selects a content replication configuration (e.g.,
where, how, when) from a plurality of available configurations that
is most efficient, expeditious, or other desired
characteristic.
[0045] In view of the exemplary systems described above,
methodologies that may be implemented in accordance with the
disclosed subject matter will be better appreciated with reference
to the flow charts of FIGS. 5-12. While for purposes of simplicity
of explanation, the methodologies are shown and described as a
series of blocks, it is to be understood and appreciated that the
claimed subject matter is not limited by the order of the blocks,
as some blocks may occur in different orders and/or concurrently
with other blocks from what is depicted and described herein.
Moreover, not all illustrated blocks may be required to implement
the methods described hereinafter.
[0046] Referring to FIG. 5, a content replication method 500 is
illustrated. At reference numeral 510, the one or more content
servers (a.k.a., distribution points, edge nodes, or staging
servers) are identified automatically for use in distributing
content to end-user devices. Selection can be based on a number of
factors pertaining to at least content servers, devices, and
content. More particularly, factors can include, but are not
limited to, available content servers, content server configuration
(e.g., hardware, software), content server location, distance
available content servers, content server configuration (e.g.,
hardware, software), content server location, distances related to
the content server (e.g., to/from content source, devices, or other
content sources), content (e.g. size, execution environment . . .
), and targeted devices. In other words, at 510 a determination is
made regarding where content should be replicated with respect to
content servers.
[0047] At numeral 520, a content replication protocol is determined
automatically for use in replicating data from one or more content
sources to one or more identified content servers. This
determination can also be based on a number of factors including
but not limited to support for certain protocols by content
servers, number of content servers targeted, location of content
servers, and the speed and reliability of a communication link
between a content source and target content server. Example
protocols can be push, pull, broadcast, and multicast, which
generally describe interaction between source and destination. For
instance, push protocol is an interaction in which the source
sends, or pushes, content to the destination, and pull protocol is
a protocol in which the destination acquires, or pulls, the content
from the source. Broadcast is similar to push except content can be
provisioned in a session that allows substantially all destinations
to acquire the content. Multicast is similar to broadcast but where
the destinations are limited. In a scenario where there is a single
content server targeted, it can be determined that push protocol is
appropriate where the communication link between the source and
target is reliable and fast, and pull protocol can preferred in the
same scenario but where the communication is unreliable or slow, so
as to avoid. Further, determining the protocol can comprise an
order of replication amongst a plurality of content servers, for
example, where some target content severs receive replicated data
from a source and subsequently operate a content source for other
content servers.
[0048] At numeral 530, a determination is made automatically as to
when content replication should be initiated based a plurality of
different factors. Some factors include whether content is required
or optional, a specified deadline, past performance, and a roaming
pattern associated with on more devices. By way of example, a
particular date and time can be selected based on a specified
deadline, the distance of a source and a content server, and the
distance of between a content server and target devices. Further,
adjustments can be made to compensate for additional time required
to reach roaming devices and potentially poor past performance.
Further yet, initiation can be performed in stages or steps to
effect a particular determined protocol.
[0049] Finally, at reference number 540, content replication can be
initiated at a determined time. More specifically, content can be
replicated to one or more identified content servers employing the
determined protocol associated with the one or more content
servers. It is also to be appreciated the method of content
replication can be semi-automatic. For example, rather that
initiating replication, information can be provided to an IT
administrator for example, who can then initiate replication or
make changes to the targeted servers, protocol, or time
determined.
[0050] FIG. 6 depicts a method 600 of content replication. At
reference numeral 610, identification of content and target devices
are received, retrieved, or otherwise obtained or acquired. For
instance, an IT administrator can specify the content and target
devices received at 610. At 620, one or more possible content
sources are identified. At numeral 630, computation of specific
weights for content servers is initiated. The specific weights
capture relevant information specific to content and targeted
devices for content servers as values that can be compared to
facilitate a decision making process. At numeral 640, one or more
content servers are selected based on specific weights and one or
more content-server-related distances such as the distance between
a content server and a source and the distance between a content
server and target devices. At reference numeral 650, a replication
protocol is determined based on factors such as the number of
selected content servers, the location of the content servers and
the quality of a communication link (e.g., reliability, bandwidth,
speed . . . ) between selected content servers and one or more
content sources. A determination is then made at 660, as to when
content replication should be initiated. Factors considered here in
include a specified deadline, past performance history, and the
roaming pattern for one or more target devices, among other things.
At reference numeral 670, content replication is initiated at the
time determined. More specifically, content is replicated to one or
more selected content servers using the determined protocol with
respect to the one or more content servers at the determined
time.
[0051] FIG. 7 is a flow chart diagram of a method 700 of relevant
data collection. At reference numeral 710, an initial weight can be
determined and assigned to a content server. The initial weight can
be a standard, non-specific weight that captures, among other
things, the capabilities, or configuration, of a content server
such as, but not limited to, the processor, memory, and storage
capacity. Furthermore, the type of a content server can be
considered, such as on premise, in the cloud, or at a third-party
location. At numeral 720, one or more distances are determined with
respect to the content server. For example, distances can be
determined between potential content sources including other
content servers and distances between content servers and devices.
In one instance, distance can be computed based on the number of
network hops on a path from a source to a destination, wherein hops
are number of intermediate computer devices (e.g., routers,
gateways . . . ) that are passed through. The weights and distances
associated with a content server are saved at 730 for subsequent
use.
[0052] FIG. 8 depicts a method of specific weight computation 800.
At numeral 810, identification of content and target devices is
received, retrieved or otherwise obtained or acquired, for example
from an IT administrator or other individual or entity. At numeral
820, initial weights for content servers are adjusted based on the
content or a new weight is produced based on the initial weight and
the content. For example, weights can be adjusted favorably for
content servers that have storage capacity capable of storing the
content. At numeral 830, weights for content servers can be
adjusted based on target devices. For instance, weights can be
adjusted favorably for content servers that are located closer to
target devices as opposed to farther away and based on the number
of target devices reachable by a content server. Accordingly, a
first content server can be weighted more favorably than a second
content server, if the first content server can reach more of the
target devices than the second content server, with all else being
equal. At reference numeral 840, any additional or custom criteria
can be considered and content server weights adjusted accordingly.
For instance, customers (e.g., businesses, organizations or other
entities that deploy the system for a purpose) can define
additional constraints or customizations according to their needs.
Additionally, an IT administrator or other person or entity can
inject knowledge into the system by way of rules or constraints.
For example, a particular content server may be off limits for data
replication for various reasons, and that fact can be reflected in
the weight associated with the content server. At numeral 850, the
specific weights for content servers can be saved. These specific
weights capture particular concerns related to content and target
devices, among other things.
[0053] FIG. 9 is a flow chart diagram of a method 900 of
distributing content to target devices. At reference numeral 910,
one or more content servers are identified. Identified content
servers include content to be distributed. At numeral 920, a
determination is made as to how to distribute or replicate content
to previously identified target devices from the one or more
identified content servers automatically. The determination can
take several factors into account including the number of target
devices, supported protocol (e.g., push, pull, broadcast . . . ),
distance between target devices and content servers, and
communication link quality, among other things. At numeral 930, a
determination is made as to when to replicate the content
automatically. Again, numerous factors can be considered including,
among others, a deadline, past performance, content priority, and
roaming pattern of one or more target devices. At numeral 940,
content is replicated or distributed to target devices utilizing an
automatically determined protocol and at an automatically
determined time.
[0054] FIG. 10 illustrates a method 1000 of change response. At
reference numeral 1010, a determination is made as to whether a
content server has been added or removed. If at numeral 1010 a
content server has not been added or removed ("NO"), the method
terminates. Alternatively, if a content server has been added or
removed ("YES"), the method continues at numeral 1020, where the
type of the content server is determined. For example, the content
server could be on premise, in the cloud, or at a third-party
location. The type of content server is typically decided by an
organization. Any time a new content is added or removed boundary
groups are adjusted, at 1030. For example, a new boundary group can
be created, where in a boundary group is a virtual demarcation
specifying groups of devices and content servers that are close in
proximity. Accordingly, a group can be created based on the
proximity of devices with respect to a new content server. At
reference numeral 1040, weights and distances can be computed. For
a new content server, an initial weight can be determined based on
factors such as the type of content server, storage capacity,
network speed to the content server, and outgoing network traffic,
among other things. The weight can simply be a number like fifty or
one hundred to facilitate comparison of content servers.
Additionally, distances can be determined with respect to a content
server such as the distance between a content server and devices or
other content servers.
[0055] FIG. 11 depicts a method 1100 of determining specific
weights for content servers. At reference numeral 1110, a
determination is made as to whether, or not, there are any content
target devices whose path of content distribution has not been
calculated. In other words, the determination pertains to whether
or not, a path has been determined from a device to one or more
content servers. This can be the case when a new device is added to
the system. More specifically, the path includes network hops or
the like from a master source to target device. In the simplest
case, the master source is the content server that directly servers
a device (1 hop). In slightly more complicated case, the master
source serves content to the content server, which serves the
content to a device (2 hops). In more complicated cases, however,
there can be additional server content servers in between, each
serving down a "tree" to each other, before the target device is
finally reached. For example, multiple content servers can pull
content from other pull content servers, which could pull from
other content servers, and so forth generating a deep tree.
[0056] If target devices have previously had their path calculated
("NO"), the method terminates. If at least one of the target
devices does not have its path calculated ("YES"), the method
continues at numeral 1120, where a first target is selected from a
list of target devices. At numeral 1130, one or more boundary
groups are determined with for the device. This can be determined
by locating one or more content server within a particular
proximity of the device. At reference 1140, a device-roaming
pattern can be determined, if possible, by analyzing past history
and identifying content servers within a predetermined proximity of
the device. At numeral 1150, one or more content servers from which
a device can acquire content are identified based on a boundary
group and a roaming pattern of the device, for example. At
reference 1160, specific weight for the one or more identified
content servers is adjusted favorably since the content servers can
reach devices targeted for content. Note that the number of target
devices that can acquire content from a particular content server
as well as how long it takes content to reach a device can be
significant factors with respect to specific weight. A
determination is made at numeral 1170 as to whether or not
additional target devices are have not yet have a path determined.
If there are additional devices ("YES"), the method proceeds to
1120 where the next device is selected in the list. Otherwise
("NO"), the method terminates.
[0057] FIG. 12 depicts a flow chart diagram of a method 1200 of
content replication. At reference numeral 1210, a determination is
made concerning whether or not to select a content server to which
content can be distributed. If yes, the method continues at 1220
where possible content sources are identified. Distances between
possible content sources and available content sources are
calculated at 1230. Next, at 1240, a content server is selected
based on distances and specific weights for content servers. For
example, a content server can be selected that is proximate to a
content source and target devices. At reference numeral 1250, a
protocol is determined for how to stage or deliver content to the
selected content server. For example, one of a push, pull, or
broadcast protocol can be selected based on what protocols are
supported by the content server, the number of target devices,
location of target devices relative to each other, and the quality
of the communication link between a source and the content server,
among other factors. After a content server is selected and
protocol determined, the method can continue at 1260, where a
determination is made as to whether or not to send instructions to
the content server. If it is determined that instructions are not
to be sent ("NO"), the method simply terminates. If it is
determined that instructions are to be sent ("YES"), for example to
notify content servers that content is available for acquisition
from a source at a particular location or when and where the
content will be broadcast, the method continues at 1270, where
instructions are sent to the content server. An acknowledgement can
be received from a content server at 1280 and the method continues
to numeral 1290. If at numeral 1290 it is determined based on the
acknowledge message that changes are not needed ("NO"), the method
terminates. Alternatively, if at numeral 1290 it is determined
based on the acknowledgement that changes are needed ("YES"), the
method proceeds to 1290 where another content server, content
source pair can be determined. Changes may be needed if the content
server indicates through the acknowledgement that it cannot reach
the source or the network connection is down, among other reasons.
Furthermore, in accordance with one implementation multiple sources
can be identified with respect to a content server, such as a
primary source and secondary source, to provide a fallback source
should content not be available to a content server from a
source.
[0058] The word "exemplary" or various forms thereof are used
herein to mean serving as an example, instance, or illustration.
Any aspect or design described herein as "exemplary" is not
necessarily to be construed as preferred or advantageous over other
aspects or designs. Furthermore, examples are provided solely for
purposes of clarity and understanding and are not meant to limit or
restrict the claimed subject matter or relevant portions of this
disclosure in any manner. It is to be appreciated a myriad of
additional or alternate examples of varying scope could have been
presented, but have been omitted for purposes of brevity.
[0059] As used herein, the terms "component" and "system," as well
as various forms thereof (e.g., components, systems, sub-systems .
. . ) are intended to refer to a computer-related entity, either
hardware, a combination of hardware and software, software, or
software in execution. For example, a component may be, but is not
limited to being, a process running on a processor, a processor, an
object, an instance, an executable, a thread of execution, a
program, and/or a computer. By way of illustration, both an
application running on a computer and the computer can be a
component. One or more components may reside within a process
and/or thread of execution and a component may be localized on one
computer and/or distributed between two or more computers.
[0060] The conjunction "or" as used in this description and
appended claims is intended to mean an inclusive "or" rather than
an exclusive "or," unless otherwise specified or clear from
context. In other words, "`X` or `Y`" is intended to mean any
inclusive permutations of "X" and "Y." For example, if "`A` employs
`X,`" "`A employs `Y,`" or "`A` employs both `X` and `Y,`" then
"`A` employs `X` or `Y`" is satisfied under any of the foregoing
instances.
[0061] Furthermore, to the extent that the terms "includes,"
"contains," "has," "having" or variations in form thereof are used
in either the detailed description or the claims, such terms are
intended to be inclusive in a manner similar to the term
"comprising" as "comprising" is interpreted when employed as a
transitional word in a claim.
[0062] In order to provide a context for the claimed subject
matter, FIG. 13 as well as the following discussion are intended to
provide a brief, general description of a suitable environment in
which various aspects of the subject matter can be implemented. The
suitable environment, however, is only an example and is not
intended to suggest any limitation as to scope of use or
functionality.
[0063] While the above disclosed system and methods can be
described in the general context of computer-executable
instructions of a program that runs on one or more computers, those
skilled in the art will recognize that aspects can also be
implemented in combination with other program modules or the like.
Generally, program modules include routines, programs, components,
data structures, among other things that perform particular tasks
and/or implement particular abstract data types. Moreover, those
skilled in the art will appreciate that the above systems and
methods can be practiced with various computer system
configurations, including single-processor, multi-processor or
multi-core processor computer systems, mini-computing devices,
mainframe computers, as well as personal computers, hand-held
computing devices (e.g., personal digital assistant (PDA), phone,
watch . . . ), microprocessor-based or programmable consumer or
industrial electronics, and the like. Aspects can also be practiced
in distributed computing environments where tasks are performed by
remote processing devices that are linked through a communications
network. However, some, if not all aspects of the claimed subject
matter can be practiced on stand-alone computers. In a distributed
computing environment, program modules may be located in one or
both of local and remote memory storage devices.
[0064] With reference to FIG. 13, illustrated is an example
general-purpose computer or computing device 1302 (e.g., desktop,
laptop, tablet, server, hand-held, programmable consumer or
industrial electronics, set-top box, game system, compute node . .
. ). The computer 1302 includes one or more processor(s) 1320,
memory 1330, system bus 1340, mass storage 1350, and one or more
interface components 1370. The system bus 1340 communicatively
couples at least the above system components. However, it is to be
appreciated that in its simplest form the computer 1302 can include
one or more processors 1320 coupled to memory 1330 that execute
various computer executable actions, instructions, and or
components stored in memory 1330.
[0065] The processor(s) 1320 can be implemented with a general
purpose processor, a digital signal processor (DSP), an application
specific integrated circuit (ASIC), a field programmable gate array
(FPGA) or other programmable logic device, discrete gate or
transistor logic, discrete hardware components, or any combination
thereof designed to perform the functions described herein. A
general-purpose processor may be a microprocessor, but in the
alternative, the processor may be any processor, controller,
microcontroller, or state machine. The processor(s) 1320 may also
be implemented as a combination of computing devices, for example a
combination of a DSP and a microprocessor, a plurality of
microprocessors, multi-core processors, one or more microprocessors
in conjunction with a DSP core, or any other such
configuration.
[0066] The computer 1302 can include or otherwise interact with a
variety of computer-readable media to facilitate control of the
computer 1302 to implement one or more aspects of the claimed
subject matter. The computer-readable media can be any available
media that can be accessed by the computer 1302 and includes
volatile and nonvolatile media, and removable and non-removable
media. Computer-readable media can comprise computer storage media
and communication media.
[0067] Computer storage media includes volatile and nonvolatile,
removable and non-removable media implemented in any method or
technology for storage of information such as computer-readable
instructions, data structures, program modules, or other data.
Computer storage media includes memory devices (e.g., random access
memory (RAM), read-only memory (ROM), electrically erasable
programmable read-only memory (EEPROM) . . . ), magnetic storage
devices (e.g., hard disk, floppy disk, cassettes, tape . . . ),
optical disks (e.g., compact disk (CD), digital versatile disk
(DVD) . . . ), and solid state devices (e.g., solid state drive
(SSD), flash memory drive (e.g., card, stick, key drive . . . ) . .
. ), or any other like mediums that can be used to store, as
opposed to transmit, the desired information accessible by the
computer 1302. Accordingly, computer storage media excludes
modulated data signals.
[0068] Communication media typically embodies computer-readable
instructions, data structures, program modules, or other data in a
modulated data signal such as a carrier wave or other transport
mechanism and includes any information delivery media. The term
"modulated data signal" means a signal that has one or more of its
characteristics set or changed in such a manner as to encode
information in the signal. By way of example, and not limitation,
communication media includes wired media such as a wired network or
direct-wired connection, and wireless media such as acoustic, RF,
infrared and other wireless media. Combinations of any of the above
should also be included within the scope of computer-readable
media.
[0069] Memory 1330 and mass storage 1350 are examples of
computer-readable storage media. Depending on the exact
configuration and type of computing device, memory 1330 may be
volatile (e.g., RAM), non-volatile (e.g., ROM, flash memory . . . )
or some combination of the two. By way of example, the basic
input/output system (BIOS), including basic routines to transfer
information between elements within the computer 1302, such as
during start-up, can be stored in nonvolatile memory, while
volatile memory can act as external cache memory to facilitate
processing by the processor(s) 1320, among other things.
[0070] Mass storage 1350 includes removable/non-removable,
volatile/non-volatile computer storage media for storage of large
amounts of data relative to the memory 1330. For example, mass
storage 1350 includes, but is not limited to, one or more devices
such as a magnetic or optical disk drive, floppy disk drive, flash
memory, solid-state drive, or memory stick.
[0071] Memory 1330 and mass storage 1350 can include, or have
stored therein, operating system 1360, one or more applications
1362, one or more program modules 1364, and data 1366. The
operating system 1360 acts to control and allocate resources of the
computer 1302. Applications 1362 include one or both of system and
application software and can exploit management of resources by the
operating system 1360 through program modules 1364 and data 1366
stored in memory 1330 and/or mass storage 1350 to perform one or
more actions. Accordingly, applications 1362 can turn a
general-purpose computer 1302 into a specialized machine in
accordance with the logic provided thereby.
[0072] All or portions of the claimed subject matter can be
implemented using standard programming and/or engineering
techniques to produce software, firmware, hardware, or any
combination thereof to control a computer to realize the disclosed
functionality. By way of example and not limitation, content
replication system 100, or portions thereof, can be, or form part,
of an application 1362, and include one or more modules 1364 and
data 1366 stored in memory and/or mass storage 1350 whose
functionality can be realized when executed by one or more
processor(s) 1320.
[0073] In accordance with one particular embodiment, the
processor(s) 1320 can correspond to a system on a chip (SOC) or
like architecture including, or in other words integrating, both
hardware and software on a single integrated circuit substrate.
Here, the processor(s) 1320 can include one or more processors as
well as memory at least similar to processor(s) 1320 and memory
1330, among other things. Conventional processors include a minimal
amount of hardware and software and rely extensively on external
hardware and software. By contrast, an SOC implementation of
processor is more powerful, as it embeds hardware and software
therein that enable particular functionality with minimal or no
reliance on external hardware and software. For example, the
content replication system 100 and/or associated functionality can
be embedded within hardware in a SOC architecture.
[0074] The computer 1302 also includes one or more interface
components 1370 that are communicatively coupled to the system bus
1340 and facilitate interaction with the computer 1302. By way of
example, the interface component 1370 can be a port (e.g. serial,
parallel, PCMCIA, USB, FireWire . . . ) or an interface card (e.g.,
sound, video . . . ) or the like. In one example implementation,
the interface component 1370 can be embodied as a user input/output
interface to enable a user to enter commands and information into
the computer 1302, for instance by way of one or more gestures or
voice input, through one or more input devices (e.g., pointing
device such as a mouse, trackball, stylus, touch pad, keyboard,
microphone, joystick, game pad, satellite dish, scanner, camera,
other computer . . . ). In another example implementation, the
interface component 1370 can be embodied as an output peripheral
interface to supply output to displays (e.g., LCD, LED, plasma . .
. ), speakers, printers, and/or other computers, among other
things. Still further yet, the interface component 1370 can be
embodied as a network interface to enable communication with other
computing devices (not shown), such as over a wired or wireless
communications link.
[0075] What has been described above includes examples of aspects
of the claimed subject matter. It is, of course, not possible to
describe every conceivable combination of components or
methodologies for purposes of describing the claimed subject
matter, but one of ordinary skill in the art may recognize that
many further combinations and permutations of the disclosed subject
matter are possible. Accordingly, the disclosed subject matter is
intended to embrace all such alterations, modifications, and
variations that fall within the spirit and scope of the appended
claims.
* * * * *