U.S. patent application number 15/663669 was filed with the patent office on 2017-11-30 for advertising campaigns utilizing streaming analytics.
This patent application is currently assigned to Excalibur IP, LLC. The applicant listed for this patent is Excalibur IP, LLC. Invention is credited to Stuart Ogawa.
Application Number | 20170345047 15/663669 |
Document ID | / |
Family ID | 48168283 |
Filed Date | 2017-11-30 |
United States Patent
Application |
20170345047 |
Kind Code |
A1 |
Ogawa; Stuart |
November 30, 2017 |
ADVERTISING CAMPAIGNS UTILIZING STREAMING ANALYTICS
Abstract
The present invention provides methods and systems for use in
advertising campaigns and advertisement targeting. Techniques are
provided in which streams of data, including communications data,
are sampled, such as during transmission to intended recipients.
Sampled data may be analyzed and used to determine topics of
interest. Sampled data may be analyzed or filtered to determine
data suspected of being of particular significance or relevance in
determining topics of interest. Determined topics of interest may
be used in advertisement targeting as part of an advertising
campaign.
Inventors: |
Ogawa; Stuart; (San Jose,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Excalibur IP, LLC |
New York |
NY |
US |
|
|
Assignee: |
Excalibur IP, LLC
New York
NY
|
Family ID: |
48168283 |
Appl. No.: |
15/663669 |
Filed: |
July 28, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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13283091 |
Oct 27, 2011 |
9754279 |
|
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15663669 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06Q 30/0241
20130101 |
International
Class: |
G06Q 30/02 20120101
G06Q030/02 |
Claims
1-20. (canceled)
21. A computerized method comprising: sampling one or more streams
of electronic data, the electronic data comprising user
communications data, to obtain sample data, wherein the sampling
comprises sensing and detecting user communications data comprising
user-generated content data streams that are in transmission to,
but not yet received by, intended recipients; analyzing the
user-generated content data streams in the sample data, wherein the
analyzing includes identifying suspect data; based on the analyzing
of the user-generated content data streams in the sample data,
modifying the sampling during at least one period based on a
determination that the suspect data is more likely to be
concentrated during the at least one period than during other
periods, wherein the modifying of the sampling is determined by
utilizing one or more analytic correlation applications in
detecting patterns, and wherein the patterns include one or more
time-based or frequency-based patterns associated with the
user-generated content data streams; based on the suspect data
obtained, selecting electronic advertisements for serving to
targeted electronic device users; and serving the selected
electronic advertisements to the targeted electronic device
users.
22. The method of claim 21, wherein multiple sampling techniques
are applied to one or more data streams.
23. The method of claim 22, wherein the multiple sampling
techniques are performed serially.
24. The method of claim 22, wherein the multiple sampling
techniques are performed in a compound manner.
25. The method of claim 22, wherein the multiple sampling
techniques are performed concurrently.
26. The method of claim 21, wherein the modifying is based on one
or more feedback mechanism predictive models or machine learning
models.
27. The method of claim 21, wherein the modifying includes
increasing one or more sampling frequencies or rates.
28. The method of claim 21, wherein the one or more streams of
electronic data are from one geographic location or from multiple
geographically distributed locations.
29. The method of claim 21, wherein the sampling comprises
monitoring, at one or more locations, the one or more streams of
electronic data during transmission.
30. The method of claim 29, wherein the sample data comprises one
or more streams of electronic data at one or more cell phone
transmission or reception nodes.
31. The method of claim 29, wherein the sample data is obtained
from one or more repeaters, computing systems, satellites,
transmission systems, or receiving systems, and wherein the sample
data may include one or more of video data, audio data, voice data,
gaming data, social networking data, or blog data.
32. The method of claim 29, wherein the sample data comprises one
or more streams of electronic data from a cloud computing database
or cloud computing data center.
33. The method of claim 21, further comprising: sampling a
plurality of streams of electronic data; and integrating data from
the plurality of streams.
34. The method of claim 21, wherein the sampling comprises
intercepting sample data related to a plurality of data modes,
wherein the data modes may comprise any of voice, audio, video,
gaming, social network or blogging.
35. The method of claim 34, further comprising sampling the one or
more streams of electronic data at one or more intervals, wherein
the one or more intervals may be determined based on one or more
parameters or one or more algorithms, and wherein the one or more
parameters or one or more algorithms may include or incorporate any
of sampling time, sampling frequency, or sampling data
analytics.
36. The method of claim 21, wherein the identifying of the suspect
data includes determining the suspect data to be of significance or
relevance in determining topics of interest to electronic device
users.
37. The method of claim 21, wherein the sampling takes place at a
same location as a data source or on a same data source system as a
data source.
38. A system comprising: one or more server computers coupled to a
network; and one or more databases coupled to the one or more
server computers; wherein the one or more server computers are
configured to: sample one or more streams of electronic data, the
electronic data comprising user communications data, to obtain
sample data, wherein the sampling comprises sensing and detecting
user communications data comprising user-generated content data
streams that are in transmission to, but not yet received by,
intended recipients; analyze the user-generated content data
streams in the sample data, wherein the analyzing includes
identifying suspect data; based on the analyzing of the
user-generated content data streams in the sample data, modify the
sampling during at least one period based on a determination that
the suspect data is more likely to be concentrated during the at
least one period than during other periods, wherein the modifying
of the sampling is determined by utilizing one or more analytic
correlation applications in detecting patterns, and wherein the
patterns include one or more time-based or frequency-based patterns
associated with the user-generated content data streams; based on
the suspect data obtained, select electronic advertisements for
serving to targeted electronic device users; and serve the selected
electronic advertisements to the targeted electronic device
users.
39. The system of claim 38, further comprising sampling the one or
more streams of electronic data via one or more devices installed
at one or more cell phone transmission or reception systems.
40. The system of claim 38, further comprising sampling the one or
more streams of electronic data from a cloud computing system or
cloud, and wherein the streams of data can include any of voice
data, video data, voice data, audio data, gaming data, social
network data, or blog data.
41. A non-transitory computer readable storage medium or media
having stored instructions thereon for causing a computer to
execute a method, the method comprising: sampling one or more
streams of electronic data, the electronic data comprising user
communications data, to obtain sample data, wherein the sampling
comprises sensing and detecting user communications data comprising
user-generated content data streams that are in transmission to,
but not yet received by, intended recipients; analyzing the
user-generated content data streams in the sample data, wherein the
analyzing includes identifying suspect data; based on the analyzing
of the user-generated content data streams in the sample data,
modifying the sampling during at least one period based on a
determination that the suspect data is more likely to be
concentrated during the at least one period than during other
periods, wherein the modifying of the sampling is determined by
utilizing one or more analytic correlation applications in
detecting patterns, and wherein the patterns include one or more
time-based or frequency-based patterns associated with the
user-generated content data streams; based on the suspect data
obtained, selecting electronic advertisements for serving to
targeted electronic device users; and serving the selected
electronic advertisements to the targeted electronic device users,
the serving including causing an advertisement serving system to
initiate or modify an automated advertising campaign that includes
the selected electronic advertisements.
Description
BACKGROUND
[0001] Effectively spending advertising dollars, from the
advertiser executive perspective, is a challenging problem.
Furthermore, even an otherwise sound advertising campaign can be
rendered ineffective by incorrect, delayed, or late to market
timing, and even very small delays can render a campaign and its
elements much less effective. This is particularly true as mobile
devices, across the globe, are used to create and transmit
real-time data. Mobile users may create and transmit data at a
materially faster rate than existing advertising platforms can
effectively intake, absorb, and process in a timely, relevant and
targeted manner, from a campaign perspective.
[0002] There is a need for more effective techniques in advertising
and advertising campaigns.
SUMMARY
[0003] Some embodiments of the invention provide systems and
methods for use in advertising campaigns, including advertisement
targeting. Techniques are provided in which streams of data,
including, for example, communications data, metadata, geo data,
temporal data, etc., is sampled, such as during transmission to
intended recipients. Sampled data may be analyzed and used to
determine topics of interest. Sampled data may be analyzed or
filtered to determine data suspected of being of particular
significance or relevance in determining topics of interest.
Determined topics of interest may subsequently be used in
advertisement targeting as part of an advertising campaign.
BRIEF DESCRIPTION OF THE DRAWINGS
[0004] FIG. 1 is a distributed computer system according to one
embodiment of the invention;
[0005] FIG. 2 is a flow diagram illustrating a method according to
one embodiment of the invention;
[0006] FIG. 3 is a flow diagram illustrating a method according to
one embodiment of the invention;
[0007] FIG. 4 is a block diagram illustrating one embodiment of the
invention; and
[0008] FIG. 5 is a block diagram illustrating one embodiment of the
invention.
[0009] While the invention is described with reference to the above
drawings, the drawings are intended to be illustrative, and the
invention contemplates other embodiments within the spirit of the
invention.
DETAILED DESCRIPTION
[0010] FIG. 1 is a distributed computer system 100 according to one
embodiment of the invention. The system 100 includes or utilizes
various computers and electronic devices. As depicted, the system
includes user computers 104, wireless devices 106, advertiser
computers 108, and server computers 110.
[0011] Furthermore, the system can include or utilize any of
numerous other distributed components. As depicted, these may
include satellites or satellite systems 112, clouds such as private
clouds 114, cell towers and related systems 116, repeaters 118,
intermediary service providers, and various forms of data 120.
[0012] Any of the various components of the system 100 may be
coupled or networked together in various ways, which may include
allowing bidirectional communication and data flow. Various
networks and types of networks may be included or utilized, which
may include telephone networks, the Internet, wired and wireless
networks, public and private networks and clouds, etc. embodiments
in which the Internet is not included, as well as embodiments in
which other networks are included in addition to the Internet,
including one more wireless networks, WANs, LANs, telephone, cell
phone, or other data networks, networks associated with satellites,
repeaters, intermediary service providers, etc. Furthermore,
embodiments are contemplated in which user computers or other
devices may be or include wireless, portable, or handheld devices
such as cell phones, smart phones, PDAs, tablets, etc.
[0013] Furthermore, while not depicted some embodiments of the
invention include one or more electronic data sampling devices or
systems, as well as other systems, devices, and components. Such
devices or systems may be separate or standalone, or may be
integrated into other computers or devices. Furthermore, such
devices and systems may be coupled, such as through one or more
networks, to other computers and devices, including the server
computers, the advertiser computers, etc.
[0014] Each of the computers may be distributed, and can include
various hardware, software, applications, algorithms, programs and
tools. Depicted computers may also include a hard drive, monitor,
keyboard, pointing or selecting device, etc. The computers may
operate using an operating system such as Windows by Microsoft,
etc. Each computer may include a central processing unit (CPU),
data storage device, and various amounts of memory including RAM
and ROM. Depicted computers may also include various programming,
applications, algorithms and software to enable searching,
sampling, search results, and advertising, such as graphical or
banner advertising as well as keyword searching and advertising in
a sponsored search context. Many types of advertisements are
contemplated, including textual advertisements, rich
advertisements, video advertisements, coupon-related
advertisements, group-related advertisements, social
networking-related advertisements, network gaming ads, virtual
world ads, user-contributed content or video, etc.
[0015] As depicted, each of the server computers 110 includes one
or more CPUs 122 and a data storage device 124. The data storage
device 124 includes a database 128 and Streaming Analytics Program
126.
[0016] As depicted, the server computer, 110, including the
Streaming Analytics Program 126, are coupled directly to various
sources of data, which may include streaming or real-time data,
including, for example, perhaps among others, satellites 112, cell
towers 116, repeaters 118 and other data 120 or data sources, which
may include other elements of the system 100, or non-depicted or
other elements. While the server computer 110 is depicted as
coupled to the data sources, in some embodiments, a streaming
analytics program or streaming analytics system may otherwise be
directly so coupled.
[0017] In some embodiments, direct or otherwise fast, efficient
connection or coupling of the Streaming Analytics Program 126 to
various data sources eliminates, reduces, mitigates or collapses
latency or ad-related latency inherent in other arrangements. For
example, ad latency increases when a data source first transmits
data, which consequently goes through a network or networks, then
arrives at an analytics system or program. By contrast, according
to some embodiments of the invention, direct connection of the
Streaming Analytics Program 126 to data sources eliminates or
reduces such latency, allowing significant immediate and downstream
advantages in advertising, such as, for example, faster
identification of relevant ad topics, faster ad selection, faster
ad delivery and campaign implementation, and, consequently,
increased timeliness, relevance, or ad performance, increased
campaign performance and ROI, etc.
[0018] The Program 114 is intended to broadly include all
programming, applications, algorithms, software and other and tools
necessary to implement or facilitate methods and systems according
to embodiments of the invention. The elements of the Program 114
may exist on a single server computer or be distributed among
multiple computers or devices.
[0019] FIG. 2 is a flow diagram illustrating a method 200 according
to one embodiment of the invention. At step 202, the method 200
includes using, one or more computers or electronic devices,
sampling one or more streams of electronic data, the electronic
data including user communications data, to obtain sample data.
Communications data or electronic data can broadly include data
such as voice data, messaging data, email data, text data, blog
data, content data, user generated content, analog data, digital
data, user-generated content data, metadata, geo data, temporal
data, etc.
[0020] It is to be noted that, in some embodiments, multiple
sampling techniques or processes, or types of sampling techniques
or processes, may be utilized, and may be performed serially,
concurrently or in a compound manner (both serially and
concurrently). Additionally, multiple testing or analytics
techniques or processes may be run on sampled data, which also may
be run serially, concurrently or in a compound manner.
[0021] At step 204, the method 200 includes, using one or more
computers, analyzing the sample data to obtain targeting data for
use in targeting electronic advertisements to electronic device
users, in which the targeting data includes data relating to topics
of interest to the electronic device users. Some embodiments, it is
noted, do not include identifying topics of interest.
[0022] At step 206, the method 200 includes, using one or more
computers, based at least in part on the targeting data, selecting
electronic advertisements for serving to targeted electronic device
users.
[0023] At step 208, the method 200 includes, using one or more
computers, serving the selected electronic advertisements to the
targeted electronic device users.
[0024] FIG. 3 is a flow diagram illustrating a method 300 according
to one embodiment of the invention. At step 302, the method 300
includes, using one or more computers or electronic devices,
sampling multiple streams of electronic data, the electronic data
including user communications data, to obtain sample data. The
sampling is conducted during transmission of the electronic data
but before reception of the electronic data by intended recipients.
Sampling includes, but is not limited to, collecting data from a
plurality of data sources, such as cell phone transmission or
reception structures, using electronic devices at the cell phone
transmission or reception structures, traditional connected
transmission channels, etc. It is to be noted that, in some
embodiments, a plurality of sampling techniques can be applied to
the same data as the data is transmitted from the data source.
[0025] Steps 304, 306 and 308 are similar to steps 204, 206 and 208
as depicted in FIG. 2
[0026] FIG. 4 is a block diagram 400 illustrating one embodiment of
the invention. Block 402 represents one or more data sources or
data streams. Data sources, among other things, cellular towers,
voice and data repeaters, cloud computing centers, publishers,
content providers, various electronic communications, etc.
[0027] Block 404 represents data sampling, including use of one or
more sensing or sampling systems. It is to be noted that, in some
embodiments, one or more sampling systems or sampling algorithms
may be utilized, or a combination of sampling algorithms may be
utilized. Furthermore, in some embodiments, a set or library of
sampling algorithms may be utilized and one or more sampling
algorithms may be selected therefrom.
[0028] At block 406, although the bulk of data is filtered and not
sampled, some data is sampled. Furthermore, from the sampled data,
suspect data is identified, which may be, for example, data
suspected of being or determined to be of particular significance
or relevance in user targeting. For some simple examples, suspect
data can be data that matches one or more keywords from a set, such
as keywords that are likely to relate to user interests, keywords
associated with possible advertisement topics, etc. In some
embodiments, all sample data may be utilized, and suspect data may
not be identified among sample data.
[0029] At block 408, advertising campaign launch or integration is
triggered, and, at block 410, sample or suspect data, or results of
analysis thereof, is fed into an advertising campaign or
advertisement targeting system(s). For example, these blocks can
include, upon sufficient collection, or collection and analysis, of
sample or suspect data, using such sample or suspect data, or the
results of analysis of such data, triggering implementation of an
ad campaign in which it will be used in ad targeting, or to trigger
integration into an ad campaign. In various embodiments, sample or
suspect data may be analyzed before triggering, feed in or
integration into an ad campaign, or may be analyzed as part of an
inventive component of such a campaign, for example. Some
embodiments include integration with existing ad campaigns,
including trafficking, analytics, billing, forecasting, targeting,
ad selection, etc.
[0030] Block 412 represents near real-time or real-time use of
sample or suspect data, or results of analysis thereof, in an ad
campaign, such as in ad targeting.
[0031] Block 420 represents one or more ad serving systems, which
may be used in serving ads and implementing ad campaigns.
[0032] Blocks 414, 416 and 418 represent prior art usage of data
not including techniques according to embodiments of the invention.
Specifically, at block 414, data is passed to traditional
applications and databases, such as database 416. At block 418, use
of such traditional techniques results in delayed campaign usage or
launch.
[0033] FIG. 5 is a block diagram 500 illustrating one embodiment of
the invention. Block 502 represents sampling, such as sampling of
data from a data stream.
[0034] Block 506 represents analysis of sample data, which can
include identification of suspect data. In embodiments, a feedback
mechanism 504 is utilized, in which sample analysis or suspect data
identification results can be used to modify influence or guide
future sampling, or sampling protocol or procedures. For example,
once suspect data, or a sufficient concentration or frequency of
suspect data, etc., is found, the feedback mechanism, which may
include models, algorithms, engines, etc., may call for, as an
example, more frequent sampling for a period thereafter, since it
may be that more suspect data is likely to be found during such a
period. Such analysis, identification and feedback mechanism can
include use of data from one or more databases or data stores, such
as database 510, as well as one or more models or algorithms 512,
which can include predictive models, machine learning models,
etc.
[0035] Block 510 represents one or more ad serving systems, which
may be utilized in serving ads and implementing ad campaigns. This
may include ad hoc, dynamic or on the fly ad generation or
selection, including streaming ads or media, based on fast or
real-time data sampling and associated analytics or algorithm
output.
[0036] Some embodiments of the invention provide systems and
methods that facilitate low to zero latency automated advertising
campaigns using real-time data sensing, sampling, and detecting
methods applied to data being created or data in transit. Systems
according to some embodiments may increase advertiser revenue, such
as by enabling the advertiser to launch automated, "first to
advertise" campaigns well in advance of competitors. Systems
according to some embodiments use a collection of methods
including, but not limited to, sensors, filters, sampling
techniques, and predictive modeling engines, for example.
[0037] Some embodiments include a recognition that effectively or
optimally spending advertising dollars, from the advertiser
executive perspective, can be a difficult and challenging problem.
Furthermore, spending advertising dollars on an otherwise good
campaign with good content can none the less result in an
ineffective or low ROI campaign if the timing is incorrect or too
slow. Late to market timing can be an enormous problem,
particularly as more mobile devices, across the globe, are used to
create and transmit real-time data. Mobile users are creating and
transmitting, which can include broadcasting, data at a materially
faster rate than existing advertising platforms generally can
intake, absorb, and process in a timely, relevant and optimal
manner, from a targeting and campaign perspective. Some embodiments
of the invention reduce the time, such as to near-zero duration
latency, such as by launching or enabling segmented and targeted
campaigns as increasingly large scale and speed data streams, or
"Big Data" streams, are occurring. For example, some embodiments,
enable, help enable, or launch extremely fast to market and
optimized targeted advertising campaigns based on real-time data,
such as cell phone communications, social networking blogs or
feeds, etc.
[0038] Some embodiments include a recognition that obtaining
relevant insights using existing systems and methods against the
increasingly large Big Data streams is no longer generally viable.
Existing advertising systems may take too much time to load
relevant Big Data, such as user and audience data, analyze the
data, give insights for advertisers to make decisions, and,
finally, to launch campaigns based on these this sequential or
waterfall processing and time intensive processes. This can result
in too many or too slow steps, which take too much time to launch
or help with a real-time, optimally targeted campaign.
[0039] Some embodiments provide new and real-time or near real-time
approaches to detect, sample, and launch timely campaigns based
upon real-time data being created or transmitted. This can enable
the advertiser the ability to launch, or have launched on the
advertiser's behalf, relevant and targeted campaigns far sooner
than competitors who use traditional methods to load and analyze
data in a database for campaign launch, targeting and
operationalization.
Some embodiments provide a real-time sampling, sensing, and
detection system capable of launching low latency advertising
campaigns, allowing near-instantaneous campaigns based on data just
being created and or just being transmitted.
[0040] Some embodiments provide techniques including a collection
of methods and subsystems using hardware, software, databases, and
modern communication methods that integrate into existing data
related systems such as cell phone transmission and reception
structures (broadly including towers, repeaters, etc.), clouds and
cloud computing systems, databases, or applications, for example.
Furthermore, some embodiments include use of real-time systems and
methods, such as real-time filters, sensors, digital processing,
and analytics, to name a few methods, to sample for relevant,
real-time, suspect target data, which suspect data can include data
that is suspected of or identified as being of particular
significance or relevance in determining topics of interest to
electronic device users. Still further, some embodiments also use
real-time systems and methods, such as real-time filters, sensors,
digital processing, and analytics, to name a few methods, to ignore
the bulk of real-time data. Additionally, some embodiments use
real-time systems and methods, such as real-time filters, sensors,
digital processing, and analytics, for example, to filter, amplify,
correlate and, examine suspect data and identify or generate
desirable targeting data, which may be, for example, relevant or
particularly relevant to a publisher or advertiser, for example.
Some embodiments further include triggering or activation, or
messaging relating to or leading to triggering or activation, of
real-time advertising campaigns.
[0041] Some embodiments include components, systems or devices that
can be placed in any of various physical or conceptual places in
the data creation, data intermediary and overall transmission
chain. In some embodiments, subsystems can be placed in multiple
distributed locations, and a central controlling system can be used
to monitor all subsystems, to perform massive and scalable data
detection, campaign launching, etc. This can improve data detection
accuracy and improve global campaign targeting, for example.
[0042] Some embodiments include systems that can identify real-time
gaps in global communication, known as imperfect information
distributions, such as by monitoring data streams and stream
activity levels, and exploit these imperfect distribution gaps to a
publisher or advertiser's advantage, for example.
[0043] Big Data creation and transmission, which can occur prior to
Big Data being traditionally captured and stored, is becoming
increasingly large and more complex as more data sources are
creating and transmitting data. Traditional processes, which may
involve capturing Big Data and then running advertising campaigns
and or running analytics against Big Data to provide segmented and
targeted campaigns, have already reached a sunset stage in terms of
capability and maturity.
[0044] Some embodiments provide systems and methods that enable
advertisers to increase topline revenue by creating campaigns fast
enough to accommodate the speed of user data creation and
transmission, as opposed to steps including waiting for the data to
be received by a publisher, then performance of analytics in order
to gain insights, and then the running of campaigns. With
traditional techniques, the first-mover opportunity and revenue, in
terms of time, can be lost.
[0045] Some embodiments include use of sophisticated digital and
analog techniques, applied to real-time data processing well into
the early data creation and transmission stream and data life
cycle, giving advertisers and publishers unprecedented marketing
speed advantages.
[0046] One Chief Marketing Officer, or CMO, ideal goal is to create
the perfect advertising campaign by defining an ideal customer
profile and surgically targeting only audiences that match ideal
customers. This perfect, albeit a utopia, state of alignment,
increases advertiser's revenue, increases advertising campaign ROI,
and reduces ad campaign expenses on campaigns targeting the
incorrect audiences as the alignment gap decreases. Providing the
right ad campaign at the earliest possible and most relevant time
can help the CMO increase revenue, including providing the right ad
at the right time, such as real-time or near real-time.
[0047] Some embodiments enable advertisers to take immediate
campaign action (or take campaign action without advertiser action)
as data is being created and or transmitted.
[0048] Some embodiments include allowing publishers and content
providers to sell premium "first to act" service levels, increasing
revenue and allowing positive differentiation from competitors.
[0049] Some embodiments reduce the time it takes for publishers and
content providers to gain insights and consequently provide premium
information services which command premium incremental revenue
streams, in a sense providing high-speed intelligence.
[0050] Techniques according to embodiments of the invention can be
implemented utilized various topologies, to globally scale into an
integrated number of installations such as cell towers, publishers
and content provider servers, clouds, data centers, and others.
[0051] While the invention is described with reference to the above
drawings, the drawings are intended to be illustrative, and the
invention contemplates other embodiments within the spirit of the
invention.
* * * * *