U.S. patent application number 11/057340 was filed with the patent office on 2005-07-07 for customer services and advertising based upon device attributes and associated distributed processing system.
This patent application is currently assigned to United Devices, Inc.. Invention is credited to Hubbard, Edward A..
Application Number | 20050149532 11/057340 |
Document ID | / |
Family ID | 34714743 |
Filed Date | 2005-07-07 |
United States Patent
Application |
20050149532 |
Kind Code |
A1 |
Hubbard, Edward A. |
July 7, 2005 |
Customer services and advertising based upon device attributes and
associated distributed processing system
Abstract
A method for providing customer services and advertising based
upon device attributes for is disclosed for a distributed
processing system. The distributed processing system identifies and
utilizes the capabilities of distributed devices connected together
through a wide variety of communication systems and networks and
utilize those capabilities to organize, manage and distribute
project workloads to the distributed devices.
Inventors: |
Hubbard, Edward A.; (Round
Rock, TX) |
Correspondence
Address: |
Kelly K. Kordzik
Winstead Sechrest & Minick P.C.
P.O. Box 50784
Dallas
TX
75201
US
|
Assignee: |
United Devices, Inc.
Austin
TX
|
Family ID: |
34714743 |
Appl. No.: |
11/057340 |
Filed: |
February 11, 2005 |
Related U.S. Patent Documents
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Application
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Filing Date |
Patent Number |
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11057340 |
Feb 11, 2005 |
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09602983 |
Jun 23, 2000 |
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11057340 |
Feb 11, 2005 |
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09538543 |
Mar 30, 2000 |
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11057340 |
Feb 11, 2005 |
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09539023 |
Mar 30, 2000 |
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11057340 |
Feb 11, 2005 |
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09539448 |
Mar 30, 2000 |
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11057340 |
Feb 11, 2005 |
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09539428 |
Mar 30, 2000 |
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11057340 |
Feb 11, 2005 |
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09539106 |
Mar 30, 2000 |
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6891802 |
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11057340 |
Feb 11, 2005 |
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09538542 |
Mar 30, 2000 |
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6654783 |
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11057340 |
Feb 11, 2005 |
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09539107 |
Mar 30, 2000 |
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Current U.S.
Class: |
1/1 ;
707/999.01 |
Current CPC
Class: |
G06F 7/00 20130101; G06F
15/16 20130101 |
Class at
Publication: |
707/010 |
International
Class: |
G06F 007/00 |
Claims
1-23. (canceled)
24. A method of operating a distributed processing system having a
network for coupling a multiplicity of Host distributed devices to
process workloads for the distributed processing system, a
plurality of Client systems requesting processing of the workloads,
and a Server system for selectively distributing the workloads from
the plurality of Client systems for processing by the distributed
processing system comprising the steps of: generating an offer to
provide processing services as an incentive for a Host distributed
device to couple to the network as one of the multiplicity of Host
distributed devices, wherein the processing services are available
only by a processing capability provided by the distributed
processing system; providing a first processing service selected
from the processing services in response to the first Host
distributed device coupling to the network to process workloads for
the distributed processing system; and updating capabilities of the
processing services in response to the first Host distributed
device coupling to the network to process workloads for the
distributed processing system.
25. The method of claim 24 further comprising the steps of: sending
an advertisement to the first Host distributed device of
recommended upgrades to capabilities the first Host distributed
device may make in exchange for access to improved processing
services from the distributed processing system; and granting an
improved processing service to the first Host distributed device in
response to a notification and verification by the Server system
that the first Host distributed device has made the recommended
upgrades.
26. The method of claim 24, wherein the Server system sends a
software agent to the first Host distributed device to monitor
operations of the first Host distributed device and request that
the distributed processing system process selected workloads in
order to enhance operations of the first Host distributed device,
wherein the software agent operates independent of a user of the
first Host distributed device.
27. The method of claim 24, wherein the first Host distributed
device is assigned a priority for sending Host workloads for
processing on the distributed processing system as an incentive for
coupling to the network to process workloads for the distributed
processing system.
28. The method of claim 27, wherein the Server system makes an
offer to sell application software to the first Host distributed
device in response to the first Host distributed device having an
assigned priority for sending Host workloads for processing on the
distributed processing system, wherein the application software
executes by processing workloads exclusively on the distributed
processing system.
29. A computer program product operating within a Server system
coupled to a network and managing a distributed processing system,
the network configured to enable the Server system to selectively
couple a multiplicity of Host distributed devices to perform
workloads for the distributed processing system, the program
product comprising a program of instructions for performing the
program steps of: generating an offer to provide processing
services as an incentive for a Host distributed device to couple to
the network as one of the multiplicity of Host distributed devices,
wherein the processing services are available only by a processing
capability provided by the distributed processing system; sending a
program providing a first processing service selected from the
processing services in response to the first Host distributed
device coupling to the network to process workloads for the
distributed processing system; and updating capabilities of the
processing services in response to the first Host distributed
device coupling to the network to process workloads for the
distributed processing system.
30. The computer program product of claim 29 further comprising
program instructions for performing the program steps of: sending
an advertisement to the first Host distributed device of
recommended upgrades to capabilities the first Host distributed
device may make in exchange for access to improved processing
services from the distributed processing system; and providing an
improved processing service to the first Host distributed device in
response to a verification that the first Host distributed device
has made the recommended upgrades to capabilities.
31. The computer program product of claim 29, wherein the Server
system sends a software agent to the first Host distributed device
to monitor operations of the first Host distributed device and
request that the distributed processing system process selected
workloads in order to enhance operations of the first Host
distributed device, wherein the requests are independent of a user
of the first Host distributed device.
32. The computer program product of claim 29, wherein the first
Host distributed device is assigned a priority for sending Host
workloads for processing on the distributed processing system as an
incentive for coupling to the network to process workloads for the
distributed processing system.
33. The computer program product of claim 32, wherein the Server
system makes an offer to sell application software to the first
Host distributed device in response to the first Host distributed
device having an assigned priority for sending Host workloads for
processing on the distributed processing system, wherein the
application software executes by processing workloads exclusively
on the distributed processing system.
34. A software agent for operation within each of a multiplicity of
Host distributed devices coupled to a network, the network
configured to enable a Server system to selectively couple the
multiplicity of Host distributed devices to perform workloads for a
distributed processing system, the software agent comprising a
program of instructions for performing the program steps of:
monitoring operations of a first Host distributed device within the
multiplicity of Host distributed devices; and generating a workload
request to the Server system for the distributed processing system
to process selected workloads in order to enhance a first operation
of the first Host distributed device in response to a user
requesting the first operation, wherein the workload request is
transparent to the user of the first Host distributed device
requesting the first operation.
35. The software agent of claim 34, wherein the first Host
distributed device receives the software agent in response to an
incentive to couple to the network as one of the multiplicity of
Host distributed devices in exchange for access to processing
services provided exclusively by a capability of the distributed
processing system.
Description
[0001] This application is a continuation-in-part application of
the following co-pending applications: application Ser. No.
09/538,543 entitled "DISTRIBUTED PARALLEL PROCESSING SYSTEM HAVING
CAPABILITY-BASED INCENTIVES AND ASSOCIATED METHOD," application
Ser. No. 09/539,023 entitled "SWEEPSTAKES INCENTIVE MODEL AND
ASSOCIATED SYSTEM," application Ser. No. 09/539,448 entitled
"CAPABILITY-BASED DISTRIBUTED PARALLEL PROCESING SYSTEM AND
ASSOCIATED METHOD," application Ser. No. 09/539,428 entitled
"METHOD OF MANAGING DISTRIBUTED WORKLOADS AND ASSOCIATED SYSTEM,"
application Ser. No. 09/539,106 entitled "NETWORK SITE TESTING
METHOD AND ASSOCIATED SYSTEM," application Ser. No. 09/538,542
entitled "NETWORK SITE CONTENT INDEXING METHOD AND ASSOCIATED
SYSTEM," and application Ser. No. 09/539,107 entitled "DISTRIBUTED
BACK-UP SYSTEM AND ASSOCIATED METHOD," each of which was filed on
Mar. 30, 2000, and each of which is hereby incorporated by
reference in its entirety.
TECHNICAL FIELD OF THE INVENTION
[0002] This invention relates to distributing project workloads
among a distributed devices and more particularly to techniques and
related methods for managing, facilitating and implementing
distributed processing in a network environment.
BACKGROUND
[0003] Prior processing systems have included the technique of
multiple users within a company sharing processing time available
on a mainframe or central processing system. Using small segments
of mainframe processing time, departments within the company would
often incur costs associated with using the processing time, which
in turn was billed back to each department from the central
information technology (IT) organization for the company. In other
instances, a company could pay for and utilize processing time made
available by third-party companies who possessed an over-capacity
of mainframe processing power. These third-party companies would,
in effect, create a market for the mainframe processing time that
went unused by the internal organizations of that third-party
company.
[0004] Prior processing techniques have also included distributed
processing projects that have utilized the Internet or World Wide
Web. These distributed processing research projects have used
personal computers (PCs) connected to the Internet to provide
processing power to accomplish research project goals. Research
project goals have been, for example, identifying large prime
numbers, analyzing radio telescope data, and analyzing code keys in
an encryption deciphering contest.
[0005] One example of a distributed processing project on the
Internet is a research project housed at the University of
California at Berkeley to analyze sky recording data gathered by
SETI (the Search for Extraterrestrial Intelligence). This sky
recording data has been gathered for some time from the large
Arecibo Radio Telescope in Puerto Rico. The processing power needed
to analyze these data recordings was very large. At the peak of
SETI's capture activities, SETI had accumulated over 100,000 years
of signals to process, as measured by the compute power necessary
to process all the signals. To analyze this data, software was
developed that could be downloaded to Internet connected PCs so
that these PCs could process small slices of these sky recordings.
In under a year, this project, called SETI@home (URL in March
2000--www.setiathome.ssl.berkeley.edu) has completely processed
this backlog of data and is now returning to the sky recording
dataset for further processing tasks. This massively parallel
distributed system has a processing throughput of over 10 TFLOPs
(terraFLOPS or 10.sup.12 floating point operations per second)
running on about 1.8 million Internet connected machines.
[0006] Another example of a distributed processing technique was
developed and implemented by Distributed.net (URL in March
2000--www.distributed.ne- t) to compete in encryption breaking
contests. Distributed.net created and distributed a client software
program which may be downloaded by client systems connected to the
Internet. This client software then acts as part of a large
distributed processing system specifically designed to break
encrypted messages on the Internet. Using this processing
technique, Distributed.net has won encryption breaking contests
sponsored by RSA Labs, which is an Internet security company. In
these contests, RSA Labs has offered a monetary prize to the winner
of the encryption contest. In organizing its efforts,
Distributed.net has offered a share of this monetary prize to the
client system that actually breaks the encryption code. In
addition, Distributed.net keeps track of overall project
statistics, as well as statistics concerning the efforts of its
client systems through individual and team rankings by amount of
processing completed.
[0007] Entropia.com (URL in March 2000--www.entropia.com) has
utilized an Internet distributed processing system to compete in
contests directed to identifying the largest prime number.
Entropia.com also offers its computing power to other research
projects. Users may sign on to be part of the distributed
processing for free. For the largest prime number contest,
Entropia.com, like Distributed.net, offers a monetary prize to the
Internet connected PC that comes up with the first prime number
achieved in a new order of magnitude. For other research projects,
the incentive is simply to be a part of the research project.
[0008] Another distributing processing web site is provided by
Process Tree Network (URL in March 2000--www.processtree.com). This
web site is attempting to sign-up Internet connected computer
systems to provide processing power for paying projects. For a
project, each partner system, when connected to the Internet, will
have client software that downloads a job unit and processes that
job unit. The incentive offered by the Process Tree Network are
"micro-payments" for the amount of work completed by any given
system. These micro-payments are apparently small amounts of some
total project value based upon the amount of the project completed
by the given system through the jobs it has processed. In addition,
each partner is given a bonus percentage of payments made to
persons they sign-up as new partners.
[0009] In completely unrelated Internet activities outside the
distributed processing arena, there have been a number of sites
that have utilized a sweepstakes model as an incentive for consumer
behavior. One of the most popular (as of March 2000) sweepstakes
sites is IWON.COM (URL as of March 2000--www.iwon.com). IWON.COM is
a standard Internet search and content portal that provides an
incentive to users by giving them entries to a sweepstakes when the
users use the portal. The more the users use the portal, the more
entries the user generates, up to a limit, for example, up to
100/day. As of March 2000, at the end of each day, IWON.COM chooses
a $10,000 winner from among the entries. At the end of each month,
IWON.COM chooses a $1,000,000 winner. And, at the end of an overall
sweeps period (as of March 2000), IWON.COM plans to draw a single
winner for a $10,000,000 grand prize. IWON.COM has created this
sweepstakes model to introduce an Internet portal in late 1999 and
make it a web site that has as a comparable number of people using
it as does Internet portals that have existed for many years, such
as, for example, Yahoo.com (URL in March 2000--www.yahoo.com).
[0010] Significantly, these prior distributed processing projects
have failed to fully utilize the capabilities of connected
distributed devices.
SUMMARY OF THE INVENTION
[0011] The present invention provides a method for providing
customer services and advertising based upon device attributes for
a distributed processing system that identifies the capabilities of
distributed devices connected together through a wide variety of
communication systems and networks and utilizes those capabilities
to organize, manage and distribute project workloads to the
distributed devices.
[0012] In one embodiment, the present invention is a method of
operating a distributed processing system, including providing a
server system, coupling the server system to a network that is
configured to be coupled to distributed devices, storing data
representing a plurality of attributes for a plurality of the
distributed devices, and utilizing at least one of the plurality of
attributes to identify a subset of the plurality of distributed
devices. More particularly, the method further includes
distributing an advertisement to the identified subset of
distributed devices, or distributing a project workload to the
identified subset of distributed devices. Still further, the
plurality of attributes includes device capability information for
the distributed devices, or information concerning users of the
distributed devices. In addition, the method may include allowing a
customer to identify an attribute to be utilized and obtaining
information about the attribute from the distributed devices.
[0013] In another embodiment, the present invention is a
distributed processing system, including a first system coupled to
a network that is configured to be coupled to distributed devices,
and a database storing attribute information for a plurality of the
distributed devices, where the first system utilizes at least one
device attribute to identify a subset of the plurality of
distributed devices. More particularly, an advertisement or a
project workload is distributed to the subset of distributed
devices. Still further, the project workload may be a human genome
analysis workload.
DESCRIPTION OF THE DRAWINGS
[0014] It is noted that the appended drawings illustrate only
exemplary embodiments of the invention and are, therefore, not to
be considered limiting of its scope, for the invention may admit to
other equally effective embodiments.
[0015] FIG. 1A is a block diagram for a distributed processing
system having client capability and incentive features, according
to the present invention.
[0016] FIG. 1B is a block diagram for information flow among
customer systems, server systems and client systems, according to
the present invention.
[0017] FIG. 2A is a block diagram for a client system, according to
the present invention.
[0018] FIG. 2B is a block diagram for processing elements within a
client system, according to the present invention.
[0019] FIG. 2C is a block diagram for a client system agent
installed on a client system, according to the present
invention.
[0020] FIG. 2D is an example user interface for a client system
agent, including incentive advertising, according to the present
invention.
[0021] FIG. 3A is a block diagram for server systems, according to
the present invention, including a control system, a sweepstakes
system and a workload database.
[0022] FIG. 3B is a block diagram for servers systems, customer
systems, client systems and outsourced host systems, according to
the present invention.
[0023] FIG. 3C is a block diagram for a server system processor,
according to the present invention.
[0024] FIG. 3D is an alternative block diagram for a server system
processor, according to the present invention.
[0025] FIG. 4 is a functional block diagram for an example
sweepstakes incentive operation according to the present
invention.
[0026] FIG. 5A is a block diagram for a distributed processing
system for a network site indexing application, according to the
present invention.
[0027] FIG. 5B is a functional block diagram for an indexing
operation according to the present invention.
[0028] FIG. 6A is a block diagram for a server system according to
the present invention, including a control system, a workload
database, and a database of client capabilities balancing
vectors.
[0029] FIG. 6B is a functional block diagram for client
capabilities balancing of workloads according to the present
invention.
[0030] FIG. 7A is a block diagram for a distributed processing
system, according to the present invention, including example
network sites on which site testing is to be conducted, such as
load testing and/or quality-of-service (QoS) testing.
[0031] FIG. 7B is a functional block diagram for site-testing,
according to the present invention.
[0032] FIG. 8 is a block diagram of a distributed processing system
for a data backup application, according to the present
invention.
[0033] FIG. 9 is a block diagram of an alternative representation
of an interconnection fabric for a distributed processing system
environment, according to the present invention.
[0034] FIG. 10 is a block diagram of a more detailed block diagram
for a client system agent installed on a client system, according
to the present invention.
[0035] FIG. 11A is a more detailed flow diagram for machine
generated sweepstakes entries according to the present
invention.
[0036] FIG. 11B is an alternative detailed flow diagram for machine
generated sweepstakes entries according to the present
invention.
[0037] FIG. 12A is a block diagram of a distributed processing
system that allows customers to select client system attributes,
according to the present invention.
[0038] FIG. 12B is a block flow diagram for client system attribute
selection, according to the present invention.
[0039] FIG. 13A is a block diagram of a distributed processing
system that provides data conversion services, according to the
present invention.
[0040] FIG. 13B is a block flow diagram for data conversion
services within a distributed processing system, according to the
present invention.
[0041] FIG. 14A is a block diagram of a distributed processing
system that provides data transmission caching, according to the
present invention.
[0042] FIG. 14B is a block diagram of a distributed processing
system that provides data sharing and file distribution, according
to the present invention.
[0043] FIG. 15 is a block diagram of an alternative representation
for a distributed processing system, according to the present
invention.
DETAILED DESCRIPTION OF THE INVENTION
[0044] The present invention contemplates the identification of the
capabilities of distributed devices connected together through a
wide variety of communication systems and networks and the
aggregation of these capabilities to accomplish processing,
storage, broadcasting or any other desired project objective. For
example, distributed devices connected to each other through the
Internet, an intranet network, a wireless network, home networks,
or any other network may provide any of a number of useful
capabilities to third parties once their respective capabilities
are identified, organized, and managed for a desired task. These
distributed devices may be connected personal computer systems
(PCs), internet appliances, notebook computers, servers, storage
devices, network attached storage (NAS) devices, wireless devices,
hand-held devices, or any other computing device that has useful
capabilities and is connected to a network in any manner. The
present invention further contemplates providing an incentive,
which may be based in part upon capabilities of the distributed
devices, to encourage users and owners of the distributed devices
to allow the capabilities of the distributed devices to be utilized
in the distributed parallel processing system of the present
invention.
[0045] The number of usable distributed devices contemplated by the
present invention is preferably very large. Unlike a small local
network environment, for example, as may be used by an Internet
Service Provider (ISP), which may include less than 100
interconnected computers systems to perform the tasks required by
the ISP, the present invention preferably utilizes a multitude of
widely distributed devices to provide a massively distributed
processing system. With respect to the present invention, a
multitude of distributed devices refers to greater than 1,000
different distributed devices. With respect to the present
invention, widely distributed devices refers to a group of
interconnected devices of which at least two are physically located
at least 100 miles apart. With respect to the present invention, a
massively distributed processing system is one that utilizes a
multitude of widely distributed devices. The Internet is an example
of a interconnected system that includes a multitude of widely
distributed devices. An intranet system at a large corporation is
an example of an interconnected system that includes multitude of
distributed devices, and if multiple corporate sites are involved,
may include a multitude of widely distributed devices. A
distributed processing system according to the present invention
that utilizes such a multitude of widely distributed devices, as
are available on the Internet or in a large corporate intranet, is
a massively distributed processing system according to the present
invention.
[0046] FIG. 1A is a block diagram for a distributed parallel
processing system 100 according to the present invention. The
network 102 is shown having a cloud outline to indicate the
unlimited and widely varying nature of the network and of attached
client types. For example, the network 102 may be the Internet, an
internal company intranet, a local area network (LAN), a wide area
network (WAN), a wireless network, a home network or any other
system that connects together multiple systems and devices. In
addition, network 102 may include any of these types of
connectivity systems by themselves or in combination, for example,
computer systems on a company intranet connected to computer
systems on the Internet.
[0047] FIG. 1A also shows client systems 108, 110 . . . 112
connected to the network 102 through communication links 118, 120 .
. . 122, respectively. In addition, server systems 104, other
systems 106, and customer systems 152 are connected to the network
102 through communication links 114, 116 and 119, respectively. The
client system capabilities block 124 is a subset of the server
systems 104 and represents a determination of the capabilities of
the client systems 108, 110 . . . 112. The incentives block 126 is
also a subset of the server systems 104 and represents an incentive
provided to the users or owners of the clients systems 108, 110 . .
. 112 for allowing capabilities of the clients systems 108, 110 . .
. 112 to be utilized by the distributed processing system 100. The
client systems 108, 110 and 112 represent any number of systems
and/or devices that may be identified, organized and utilized by
the server systems 104 to accomplish a desired task, for example,
personal computer systems (PCs), internet appliances, notebook
computers, servers, storage devices, network attached storage (NAS)
devices, wireless devices, hand-held devices, or any other
computing device that has useful capabilities and is connected to a
network in any manner. The server systems 104 represent any number
of processing systems that provide the function of identifying,
organizing and utilizing the client systems to achieve the desired
tasks.
[0048] The incentives provided by the incentives block 126 may be
any desired incentive. For example, the incentive may be a
sweepstakes in which entries are given to client systems 108, 110 .
. . 112 that are signed up to be utilized by the distributed
processing system 100. Other example incentives are reward systems,
such as airline frequent-flyer miles, purchase credits and
vouchers, payments of money, monetary prizes, property prizes, free
trips, time-share rentals, cruises, connectivity services, free or
reduced cost Internet access, domain name hosting, mail accounts,
participation in significant research projects, achievement of
personal goals, or any other desired incentive or reward.
[0049] As indicated above, any number of other systems may also be
connected to the network 102. The element 106, therefore,
represents any number of a variety of other systems that may be
connected to the network 102. The other systems 106 may include
ISPs, web servers, university computer systems, and any other
distributed device connected to the network 102, for example,
personal computer systems (PCs), internet appliances, notebook
computers, servers, storage devices, network attached storage (NAS)
devices, wireless devices, hand-held devices, or any other
connected computing device that has useful capabilities and is
connected to a network in any manner. The customer systems 152
represents customers that have projects for the distributed
processing system, as further described with respect to FIG. 1B.
The customer systems 152 connect to the network 102 through the
communication link 119.
[0050] It is noted that the communication links 114, 116, 118, 119,
120 and 122 may allow for communication to occur, if desired,
between any of the systems connected to the network 102. For
example, client systems 108, 110 . . . 112 may communicate directly
with each other in peer-to-peer type communications. It is further
noted that the communication links 114, 116, 118, 119, 120 and 122
may be any desired technique for connecting into any portion of the
network 102, such as, Ethernet connections, wireless connections,
ISDN connections, DSL connections, modem dial-up connections, cable
modem connections, fiber optic connections, direct T1 or T3
connections, routers, portal computers, as well as any other
network or communication connection. It is also noted that there
are any number of possible configurations for the connections for
network 102, according to the present invention. The client system
108 may be, for example, an individual personal computer located in
someone's home and may be connected to the Internet through an
Internet Service Provider (ISP). Client system 108 may also be a
personal computer located on an employee's desk at a company that
is connected to an intranet through a network router and then
connected to the Internet through a second router or portal
computer. Client system 108 may further be personal computers
connected to a company's intranet, and the server systems 104 may
also be connected to that same intranet. In short, a wide variety
of network environments are contemplated by the present invention
on which a large number of potential client systems are
connected.
[0051] FIG. 1B is a block diagram for information flow 150 among
customer systems 152, server systems 104 and client system 134,
according to the present invention. The server systems 104, as
discussed above, may include any number of different subsystems or
components, as desired, including client system capabilities block
124 and incentives block 126. The server systems 104 send project
and benchmark workloads 130 to client systems 134. A benchmark
workload refers to a standard workload that may be used to
determine the relative capabilities of the client systems 134. A
project workload refers to a workload for a given project that is
desired to be completed. The project workload may be, for example,
a workload for projects such as network site content indexing,
network site testing including network site load testing and
network site quality of service testing, data back-up, drug design,
drug interaction research, chemical reaction studies,
bioinformatics including genetic and biological analyses, human
genome analyses, pair-wise comparisons including fingerprint and
DNA analyses, data mining, internet hosting services, intranet
hosting services, auction services, market clearing services,
payment systems, bioinformatic simulations, knowledge management
services, trading services, data matching services, graphics
rendering, or any other desired project.
[0052] Client systems 134, as discussed above, may be any number of
different systems that are connected to the server systems 104
through a network 102, such as client systems 108, 110 . . . 112 in
FIG. 1A. The client systems 134 send results 132 back to the server
systems 104 after the client systems 134 complete processing any
given workload. Depending upon the workload project, the server
systems 104 may then provide results 156 to customer systems 152.
The customer systems 152 may be, for example, an entity that
desires a given project to be undertaken, and if so, provides the
project details and data 158 to the server systems 104.
[0053] FIG. 2A is a block diagram for an example client system 108
according to the present invention. In this simplified block
diagram, an original workload 204 is received through line 208 from
an interface 206. The original workload 204 represents a portion of
the processing, storage or other activity required to complete the
desired task for which the server system 104 is trying to
accomplish. This original workload 204 is sent by the server system
104 through the network 102 and received by the client system 108
through communication link 118. The client system 108 processes the
original workload 204. Following line 212, results 202 are then
stored for transferring along line 210 to interface 206. Interface
206 may then communicate the results back to the server system 104
through communication line 118, or to other client systems (for
example, with peering of client systems) and then through the
network 102.
[0054] It is noted that the workload received by client system 108
and the processing or activity performed may depend up a variety of
factors, as discussed further below. In part, this workload
allocated by the server system 104 to each client system 108, 110
and 112 may depend upon the capabilities of the client system, such
as the processing power, disk storage capacity, communications
types, and other capabilities available from the various components
of the systems within the client system 108.
[0055] The server systems 104 can select the workloads for the
client system 108 and may control when these workloads are
performed, through operational code (i.e., an agent) residing and
installed on the client system 108. Alternatively, the owner or
user of the client system 108 may determine when workloads are
procured or obtained from the server systems 104, as well as when
these workloads are performed, for example, by accessing the server
systems 104 through the network 102. For example, the sever system
104 may download to the client system 108 upon request one or more
workloads. At the same time, an agent residing on the client system
108 may operate to process the workload or multiple workloads
downloaded to the client system 108. It is noted, therefore, that
the agent may be simultaneously managing more than one workload for
any number of projects. When the workload is complete, the agent
may inform the owner or user of the client system 108 the results
are ready to be communicated back. The client system 108 may then
upload results to the server system 104 and download new workloads,
if desired. Alternatively, these logistical and operational
interactions may take place automatically through control of the
agent and/or the server systems 104.
[0056] FIG. 2B is a block diagram for processing elements within a
client system 108 according to the present invention. In this
diagram, client system 108 is contemplated as a personal computer.
In a personal computer, an internal bus 260 would typically have a
variety of different devices connected to it. For example, a CPU
250 could be connected through the bus 260 to a video processor
252, a floating point processor 254 (often integrated within the
CPU itself), and digital signal processors (DSPs), such as those
found on sound cards and modems. In addition, any of a variety of
other processing devices 258 may be included. Furthermore, other
types of devices may be connected, such as hard drives 264, which
provide disk storage capabilities, and a digital camera 262.
[0057] It is noted, therefore, that the capabilities for client
systems 108, 110 . . . 112 may span the entire range of possible
computing, processing, storage and other subsystems or devices that
are connected to a system connected to the network 102. For
example, these subsystems or devices may include: central
processing units (CPUs), digital signal processors (DSPs), graphics
processing engines (GPEs), hard drives (HDs), memory (MEM), audio
subsystems (ASs), communications subsystems (CSs), removable media
types (RMs), and other accessories with potentially useful unused
capabilities (OAs). In short, for any given computer system
connected to a network 102, there exists a variety of capabilities
that may be utilized by that system to accomplish its direct tasks.
At any given time, however, only a fraction of these capabilities
are typically used on the client systems 108, 110 . . . 112. The
present invention can take advantage of these unused
capabilities.
[0058] It is also noted that along with receiving the workload, the
client system 108 will also receive an agent that manages the
completion of the workload. This agent may be software that is
customized for the particular computer system and processing
capabilities of the client system 108. For example, if the client
system is a personal computer as shown in FIG. 2B, the agent may be
a program that operates in the background of the computer's
operating system. When the agent determines that there is unused
processing or other capabilities, the agent may take advantage of
it. For example, if the user is using a word processing application
to create a document, little processing power is being utilized by
the word processing program, leaving the computer's CPU and video
processor underutilized. Thus, the agent could execute commands to
these processors during dead cycles. In this way, the agent may
facilitate the completion of workload processing in a reduced time.
In addition, this agent may be self-updating upon connecting to the
server systems 104, so that the agent may be kept up to date with
current software revisions and workload activities. It is also
noted that the agent may manage work on multiple workloads at the
same time, so that any given distributed device connected to the
network 102 may be working on a plurality of workloads at any given
time.
[0059] FIG. 2C is a block diagram for an example client system
agent 270. The agent 270 may include a security subsystem 272 that
controls the interface of the client system 108 with the agent 270.
The security subsystem 272 may help keep the workloads secure and
may help to keep the client systems 108 from suffering any security
problems in completing the workload. For example, the agent 272 may
operate to keep viruses from attacking the client system 108 while
the client system 108 is processing the workload through the
operation of the agent. The security subsystem 272, therefore, may
provide the interface for the workloads 130 and the results
132.
[0060] The clients system agent 270 may also include a workload
engine 274, a statistics/user interface/incentive advertising block
276, and a workload package and update processing block 278. In the
example shown in FIG. 2C, workloads 130 pass through the security
subsystem 272 and along line 280 to the workload package and update
processing block 278. In this block 278, the agent 270 may be
updated by the server systems 104. Alternatively, the agent 270 may
determine, when connected to the server systems 104, whether it
needs to be updated and then accomplish that updating
automatically. Once the workload package is processed, the workload
engine 274 may receive the workload following line 288. The
workload engine 274 works on the workload, ultimately completing
the workload. The results or status of the workload may then be
sent through the security subsystem 272 following line 282. The
results 132 may then be provided back to the server systems
104.
[0061] The statistics/user interface/incentive advertising block
276 may provide workload, incentive and other statistics, as well
as any other desired interface features, to the user of the client
system. For example, the block 276 may show a user the expected
amount of processing time it will take for the client system to
complete a workload task based upon the capabilities of the system.
As also shown, the block 276 may receive information following
lines 286 and 284 from the workload package and update processing
block 278 and from the workload engine 274. If desired, security
information from the security subsystem 272 could also be displayed
to the user of the client system. It is noted that the information
displayed to the user of the client system may be modified and
selected as desired without departing from the present
invention.
[0062] With respect to incentive advertising, the block 276 may
also show the user of the client system how this processing time
might change depending upon various possible upgrades to the
capabilities of the client system, such as a faster microprocessor,
more memory, more disk storage space, etc. Furthermore, the client
system capabilities may be shown correlated to the incentives
provided to the client system for participation. Thus, the user may
be provided information as to how the user's incentives would
increase or change depending upon other computer systems or
upgraded capabilities the user could acquire. This incentive value
increase may also be tied to upgrades to particular vendor's
devices. For example, if the user's device is a computer system
having an ABC microprocessor, the block 276 may provide the user
information as to increased incentive values based upon an upgrade
to a more powerful ABC microprocessor. Similarly, if the user's
device is a computer system obtained from ABC, the block 276 may
provide the user information as to increased incentive values based
upon an upgrade to a more powerful ABC computer system.
[0063] FIG. 2D is a an example user interface 276 for a client
system agent, including incentive advertising, according to the
present invention. In the example shown, interface 276 is a window
230 that may be displayed on a distributed device, for example, a
computer system. This window 230 displays the desired information
for the agent client manager. As indicated above, this agent client
manager is initially downloaded from the server systems 104 and
thereafter may be updated at various times when the client system
is communicating with the server systems. The interface 276, as
shown, includes interface tabs 221, 222, 224, 226, 228, 244, 246
and 248. These interface tabs may be selected through the user of a
pointing device or keyboard attached, for example, to a computer
system graphically displaying the window 230. It is noted that the
interface tabs 221, 222, 224, 226, 228, 244, 246 and 248 are only
examples, and the number, arrangement and content of tabs may be
modified as desired. In addition, the example user interface 276
depicted in FIG. 2D is only an example and may be modified as
desired.
[0064] In FIG. 2D, the processor values interface tab 224 is the
one currently selected by the user. This tab 224 (Processor Values)
includes example information that may be displayed to the user.
Assuming that a workload is being processed by the agent client
manager, the user may select the button 242 (Show My Incentive
Values) to show the user's current incentive values associated with
the workload being performed. The personal incentive values chart
232 (My Personal Incentive Values) may then be displayed to the
user. As shown, the incentive values are provided in a relative
scale from 1 to 10. The key designation 240 represents the
incentives associated with the users current central processing
unit (CPU) or microprocessor.
[0065] As indicated above, this incentive information may also be
tied to the specific vendor of the user's CPU, for example, ABC
Company's CPU. Thus, as shown, the key designation 240 (My current
processor) and the corresponding bar graph portion 236 represent
incentives for the user's current CPU (e.g., a 166 MHz processor).
The key designation 238 represents the incentives that the user is
projected to have if the user were to upgrade the CPU. Again, this
upgrade incentive information may be tied to the specific vendor of
the user's CPU or to any other vendor, if desired. Thus, as shown,
the key designation 238 (NEW ABC 1 GHz processor!) and the
corresponding bar graph portion 234 represent incentives for an
upgrade to a new ABC CPU (e.g., a new ABC 1 GHz processor). In this
manner, a user may be provided an incentive to increase the
capabilities of the distributed device, and a vendor may be
provided advertising so that the user is also directed to a
particular upgrade.
[0066] Looking further to FIG. 2D, other similar incentive related
information tabs may be provided for any desired capability of the
distributed device. For example, tab 246 (Memory Values) represents
information that may be provided for the memory capabilities of the
distributed device. Tab 224 (Graphics Values) represents
information that may be provided for the graphics capabilities of
the distributed device. Tab 226 (Communications Values) represents
information that may be provided for the communication capabilities
of the distributed device. Tab 228 (Storage Values) represents
information that may be provided for the storage capabilities of
the distributed device. Tab 248 (System Values) represents
information that may be provided for the system capabilities as a
whole for the distributed device.
[0067] In addition to these incentive related information tabs,
other tabs may be included to provide information and control for
any desired features of the agent client manager. For example, the
tab 244 (Current: Prime Search) represents information that may be
displayed to the user about the current workload being performed by
the agent client manager, for example, a search for large prime
numbers. The tab 221 (Settings) represents information that may be
displayed to the user about various settings for the client agent
manager. In particular, the tab 221 may provide the user the
ability to control any desired aspect of the operation of the agent
client manager. For example, the user may be able to select a
portion of the capabilities that may be utilized (e.g., a maximum
of 20% of the system memory), the types of workloads that may be
performed (e.g., only scientific research projects), the times when
the agent may utilize system resources (e.g., only between 12 to 6
am, or only when the system is idle), or any other desired
operational feature. It is noted that in addition to upgrade
incentive information indicated above, the user may also be
provided information as to how incentives would increase if the
user allocated or changed the settings for the agent client
manager.
[0068] This user selection of operational features allows for
workloads to be scheduled or balanced based upon user input and
desires. These user vectors, as indicated above, would allow users
to dedicate their device capabilities to specific research projects
(cancer, Parkinson's disease, Internet, genetics, space science,
etc.), to specific non-profit or for profit organizations
(Greenpeace, Celera, etc.), educational institutions (University of
Texas), a specific group of like minded users, or any other entity
or endeavor. This affiliation selection allows the distributed
processing system to automatically include a user's device
capabilities in a pool dedicated to the chosen affiliation.
Additionally, a user could choose to mix various percentages and
allocations of device capabilities among multiple affiliations. It
is noted that the user need not make any affiliation selection and
need not allocate 100 percent of device capabilities. Rather, only
a portion of the device capabilities may be allocated to a
particular affiliation, leaving the remainder non-allocated and not
affiliated. The capability allocation may also be a system-wide
(i.e., course) allocation, such as some desired percent of overall
device capabilities. The capabilities allocation may also be
subsystem specific (i.e., fine) allocation, such as allocation of
particular subsystem capabilities to particular affiliations.
[0069] Now looking to FIG. 3A, the server systems 104 may be one or
more computer systems that operate to identify client system
capabilities, organize workloads, and utilize client systems to
accomplish a desired task. The server systems 104 includes a
control system 304 a workload database 308, and a sweepstakes
system 306, as discussed more below. The workload database 308
stores any desired project task, which may be broken up into
discrete workload tasks WL1, WL2 . . . WLN, as represented by
elements 336, 338 . . . 340. The workload database may also store
one or more benchmark workloads (BWL) 335 that may be utilized to
determine client system capabilities in response to a standard
workload. Through line 312, the workload database 308 communicates
with control system 304. Control system 304, for example, receives
original workload 322 and transfers it to the interface 320 through
line 330. The interface 320 then transfers the workload 322 to the
network 102 through line 114. This workload 322 is ultimately
received as workload 204 by client system 108, 110 or 112, as shown
in FIG. 2A. The result 324 is ultimately received by the control
system 304 through interface 320 and line 328.
[0070] In allocating workloads, the control system 304 may consider
the capabilities of the client systems 108, 110 and 112 to which
the control system 304 is sending workloads. For example, if client
108 has more processing power than client 110, the control system
304 may allocate and send more difficult or larger workloads. Thus,
client 108 may receive WL1 336 and WL2 338, while client 110 would
only receive WL3. Alternatively, the workload database 308 could be
organized with differing levels of processing power or capability
requirements for each workload. In this way, WL1 336 may represent
a greater processing or system capability requirement than WL2 338.
It should be noted that workload may be a processing task, a data
storage task, or tied to any other of a variety of capabilities
that may be utilized on the client systems 108, 110 . . . 112.
[0071] As indicated above, to encourage owners or users of client
systems to allow their system capabilities to be utilized by
control system 104, an incentive system may be utilized. This
incentive system may be designed as desired. Incentives may be
provided to the user or owner of the clients systems when the
client system is signed-up to participate in the distributed
processing system, when the client system completes a workload for
the distributed processing system, or any other time during the
process. In addition, incentives may be based upon the capabilities
of the client systems, based upon a benchmark workload that
provides a standardized assessment of the capabilities of the
client systems, or based upon any other desired criteria.
[0072] One example use of a benchmark workload is to use the
benchmark workload to determine incentive values. For example, the
server systems 104 may be designed to send out a standard benchmark
workload once an hour to each client system 108, 110 . . . 112. If
a client system is not available at that time for any reason, the
workload would not be completed by the client system, and there
would be no incentive value generated for that client system. In
this example, the benchmark workload may be a timed work-set that
would exercise each subsystem with capabilities within the client
system that was desired to be measured. A more capable client
system would then generate greater incentive values from executing
the benchmark workload, as compared to a lesser capable client
system. These incentive values may be utilized as desired to
determine what the client system should get in return for its
efforts. For example, if the incentive were a sweepstakes as
discussed further below, the number of entries in the sweepstakes
may be tied to the system's performance of the benchmark workload.
Thus, the faster or better the client system performs the benchmark
workload, the more entries the client system would receive.
[0073] In the embodiment shown in FIG. 3A, the server systems 104
includes a sweepstakes system 306 that functions with control
system 304 to provide incentives for the users or owners of client
systems 108, 110 and 112 to allow their system capabilities to be
used by the server systems 104. The control system 304 may
determine a sweepstakes entry value 302 that is sent along line 310
to the sweepstakes system 306. The sweepstakes system 306 may then
receive sweepstakes entry 332 and provide it to the sweepstakes
engine 330 through line 334. The sweepstakes engine 330 may process
the entries and determine a winner, when desired. In the embodiment
shown, therefore, entries to the sweepstakes may be generated each
time a unit of work is accomplished by one or more of the
subsystems within a client system 108, 110 or 112 via an agent
installed on the device for the purposes of managing and completing
units of work. The total entries for any period of time would,
therefore, be dynamic depending on how many are received. Odds of
winning would then be determined by the total number of entries
received and the total number of entries contributable to any given
entrant.
[0074] FIG. 3B is another example block diagram of a distributed
processing system 300 including servers systems 104, customer
systems 152, client systems 134 and out-sourced host systems 340,
according to the present invention. The servers systems 104 may
include an analytic subsystem 346, a results/workload production
subsystem 344, a project pre-processing subsystem 342, a client
agent subsystem 243, and an incentive advertising subsystem 245.
The incentive advertising subsystem 245 may operate to provide
advertising information, for example, the upgrade incentive
information as discussed with respect to FIG. 2D. The client agent
subsystem 243 may operate to download an agent to the client
systems 134 and to update this agent at times when the server
systems 104 are communicating with the client systems 134.
[0075] The customer systems 152, which represent customers that
have projects that they desired to be processed by the distributed
processing system, may be connected to the project pre-processing
subsystem 342 to provide projects to the servers systems 104. These
projects are processed by the project pre-processing subsystem 342
and passed to the results/workloads production subsystem 344, which
produces and sends out workloads 130 and receives back results 130.
The analytic system 346 then takes the results and processes them
as desired. Completed project information may then be provided from
the analytic system 346 to the customer systems 152. In this
manner, the projects of the customer systems 152 may be processed
and project results reported by the distributed processing system
of the present invention.
[0076] Also, as shown, the workloads 130 and the results 132, or
other tasks of the server systems 104, may be processed and handled
by out-sourced host systems 340, if desired. Thus, some or all of
the workloads 130 may be sent first to out-sourced host systems
340. Out-sourced host systems 340 then send workloads 130A to the
client systems 134 and receive back results 132A. The out-sourced
host systems 340 then send the results 132 back to the server
systems 104. It is noted that this out-sourcing of server system
tasks may be implemented as desired for any given task that the
server systems 104 may have. It is further noted that, if desired,
the server systems 104 may perform all of the desired functions of
the server systems 104 so that no out-sourced host systems 340
would be used.
[0077] FIG. 3C is a block diagram for one embodiment of a server
system processor 350, according to the present invention. An agent
abstraction layer 360 may send workloads 130 and receive results
132. The security subsystem 354 may interact with the agent
abstraction layer 360 and provide information to a data parser 352
and an application programming interface (APIs) block 356. The APIs
block 356, the data parser 352 and a workload manager 558 may
interact to accomplish the desired tasks for the server system
processor 350. It is noted that for this embodiment, the API
protocol could be controlled and provided to other host
systems.
[0078] FIG. 3D is an alternative block diagram for a server system
processor 350, according to the present invention. In this
embodiment, the APIs block 356 and the agent abstraction layer 360
are not present. The data parser 352, the workload manager 358 and
the security subsystem 354 interact to provide the desired server
system tasks. It is noted that for this embodiment, the security
subsystem is controlled and utilized for communicating with client
systems.
[0079] FIG. 4 is a functional block diagram for a sweepstakes
operation 400 by the system server 104 according to the present
invention. In block 402, the server systems 104 may sign-up client
systems in "accept clients" block 402. Following line 418, the
server systems 104 identifies the capabilities of the client's
computer and processing systems in the "determine client system
capabilities" block 404. Control passes along line 420 to the
"distribute workloads to client systems" block 406, where the
server systems 104 allocates workloads to each client system 108,
110 and 112. This workload may also be an benchmark workload, as
indicated above, that acts as an entry workload to determine the
entries or entry values for the client system. As also indicated
above, in distributing the workloads in block 406, the server
system 104 may take into consideration the capabilities of the
client systems to which workloads are being distributed. The client
systems 108, 110 and 112 then operate to complete the workloads
allocated to them. The server system 104 receives back workload
results in "receive workload results" block 408.
[0080] At this point, control passes along line 424 to the
"determine sweepstakes entries" block 410. In this block 410, the
server system 104 determines the entry value for the workload
completed or for a standard benchmark or entry workload completed.
This entry value may be weighted upon a variety of factors
including factors such as the amount of work completed, the
difficulty level of the processing required, and the accuracy of
the results. It is noted that any desired weighting may be
utilized. Thus, it is understood that a wide variety of
considerations may be utilized to determine the entry value
weighting for the sweepstakes.
[0081] Although the weighting determination is shown in block 410
in FIG. 4, the entry value may also be determined, in whole or in
part, when a client system signs on to the distributed processing
distributed system of the present invention. For example, if a
client system has state-of-the-art CPU, video processor, DSP
engine, memory, and large amounts of free disk storage space, a
high entry value may be allocated to this client system up-front.
In contrast, a client system that has a slow CPU, a weak video
processor, no DSP engine, little memory, and little free disk
storage space may be allocated a small entry value. In this way,
the owners or users of the client systems may be provided immediate
feedback as to the potential sweepstakes entry value of their
computer systems, devices and system capabilities.
[0082] It is further noted that the entry value may take any
desired form and may be, for example, a multiplier that will be
used for each unit of workload completed. In this way, the owner or
user will readily be cognizant that a state-of-the-art system will
yield a high multiplier, where as an older system, system
capability or device will yield a low multiplier. Such feedback,
whether communicated to the owner or user immediately upon signing
up or upon completion of each workload, will create an incentive
for owners and/or users to acquire state-of-the-art systems,
thereby further increasing the potential processing power of the
distributed processing system of the present invention.
[0083] In addition, different workload projects may be designated
with different entry values, as well. For example, some workload
projects may require particular hardware or software processing
systems within a client system or device. Thus, the number of
client systems that are capable of performing the task would be
limited. To further encourage participation by those owners or
users with capable systems, the entry value for taking on
particular workloads and/or systems with the desired features may
be allocated higher entry values.
[0084] Referring back to FIG. 4, control passes along line 426 to
the "process entries" block 412. In this block 412, the sweepstakes
entries are processed and stored as desired. Following line 428,
"end of entry period" decision block 414 represents a determination
of whether the time for getting entries into the sweepstakes has
ended. If not, the control continues to line 430 and back to blocks
402, 404 and/or 406, depending upon what is desired. Once the entry
period has ended, control flows along line 432 to "determine
winners" block 416. The server system 104 then identifies from
among the entries, who the winning client system or systems will
be.
[0085] The entry period may be any desired time frame and may
include multiple overlapping time frames, as desired. For example,
winners may be determined daily for entries each day, monthly for
entries within a month, and/or yearly for entries within one year.
In addition, special entry periods may be generated, if desired,
for example where a particularly important workload project had a
short time frame in which it needed to be completed.
[0086] FIGS. 1, 2A-C, 3A-D, and 4 are directed to example
embodiments for a distributed processing system according to the
present invention, including a sweepstakes reward or incentive
feature, as shown in the embodiments of FIG. 3A and FIG. 4.
[0087] FIGS. 6A and 6B further describe a capabilities scheduling
feature, in which the server systems 104 may identify and consider
any of a variety of client system capability vectors in determining
how to organize, allocate and manage workloads and projects. FIGS.
5A and 5B describe a distributed processing system and workload
project that accomplishes network site indexing. FIGS. 7A and 7B
describe a distributed processing system and a workload project
that accomplishes network site testing, such as quality of service
(QoS) testing and load testing. And FIG. 8 describes a distributed
processing system, preferably with respect to a corporate intranet,
that accomplishes distributed data back-up.
[0088] FIG. 9 is an alternative representation for the
interconnection fabric for a distributed processing system
environment and describes idle client system identification and
shared component client systems. FIG. 10 describes a client system
agent installed on a client system. FIGS. 11A and 11B further
describe machine generated sweepstakes entries. FIGS. 12A and 12B
describe client capability selection features. FIGS. 13A and 13B
describe data conversion services. FIG. 14A describes a distributed
processing system that provides data transmission caching. FIG. 14B
describes a distributed processing system that provides data
sharing and file distribution functions. And FIG. 15 describes an
alternative representation for a distributed processing system,
according to the present invention.
[0089] Looking now to FIG. 5A, block diagram is depicted of a
distributed processing system 550 for a network site indexing
application, according to the present invention. As stated above
with respect to FIG. 1A, the network 102 may be a wide variety of
networks. For this network site indexing application, the network
102 may preferably be the Internet having a multitude of network
sites 552 . . . 554. Each network site 552 . . . 554 may have a
variety of different content types that may be indexed, ranging
from complex sites to relatively simple sites. For example, network
site 552 includes text 570A, images 570B, audio streams 570C, video
streams 570D, files 570E and other content 570F. Network site 554
is less complex and includes text 572A, images 572B, and other
content 572C. Both network sites 552 and 554 are connected to the
network 102 through communication lines 558 and 556,
respectively.
[0090] As discussed above, the server systems 104 manage workloads
for the client systems 108, 110 . . . 112. The client systems 108,
110 . . . 112 process these workloads and produce indexing results.
The resulting index may be stored at a centrally managed site, such
as central index storage block 560, or may itself be distributed
over the possibly millions of indexing clients 108, 110 . . . 112,
as shown by remote index storage blocks 562, 564 . . . 566. If
remote index storage is utilized, a master database content index
may be stored locally, for example, in the central index storage
block 560. This content index may then direct relevant searches to
the distributed massively parallel engine for search queries.
[0091] Referring now to FIG. 5B, a functional block diagram is
shown for a network site indexing operation 500 according to the
present invention. As described in FIG. 1A with respect to other
systems 106, there may be any number of computer and processing
systems connected to the network 102. Any one of these others
systems 106 may publish information on the network 102 for access
by any other system connected to the network 102. This information
to be indexed may take a wide variety of forms, including, for
example, text, images, audio streams, video streams, databases,
spreadsheets, PDF files, Shockwave data, Flash data, applications,
data files, chat streams, or any other information, data or data
streams that may be accessible on a network site. The distributed
processing system of the present invention may have as a workload
the task of indexing this potentially massive amount of
information.
[0092] For example, where the network 102 is the Internet or a
large intranet, a large amount of processing power and time is
needed to create an accurate, complete and up-to-date index of the
information. The Internet uses an IP (Internet Protocol) address
protocol to direct traffic around the Internet. The IP address is
the address of a computer attached to a TCP/IP (Transmission
Control Protocol/Internet Protocol) network. Every system on the
network must have a unique IP address. IP addresses are typically
written as four sets of numbers separated by periods. The TCP/IP
packet uses 32 bits to contain the IP address, which is made up of
a network and host address (NETID and HOSTID). The more bits used
for network address, the fewer remain for hosts. Web pages within a
particular web site with a unique address may be addressed through
URLs (Uniform Resource Locator) associated with that web site. In
short, there is a limited, but very large, number of possible IP
addresses for uniquely identifiable Internet sites that may be
accessed and analyzed to generate an index of Internet sites and
web pages via URLs.
[0093] The operation diagram of FIG. 5B starts with the "clients
receive indexing workloads" block 502. In this block, the system
server 104 provides the clients systems 108, 110 . . . 112 with a
workload task to index a portion of the information accessible on
the network 102. For example, with the Internet, each workload may
be single IP address or groups of URLs or, in some cases, large
data types contained on single sites or pages. Following line 514,
the "clients interact with other systems" block 504 represents the
operation of the agent installed on the client systems 108, 110 . .
. 112 to access the network sites, according to the assigned
workload, and index the information accessible on that site. This
indexing may include all types of information accessible on that
site, including text, audio, image, video, etc.
[0094] Next, following lines 516 and 518, the client systems 108,
110 and 112 complete the workload tasks, get the results ready for
transmission, and sends those results back to the system server 104
in "clients complete workload" block 506 and "indexing results sent
to server system" block 508. Control passes along line 520 to
"index compiled for use" block 510 where the server system formats
and/or compiles the results for use. For example, the index results
may be utilized for accurate, complete and up-to-date search
information for the network 102. As indicated with respect to FIG.
5A, the resulting index may be stored remotely or locally following
line 522. Thus, element 524 represents remote storage of the index,
and element 526 represents central storage of the index. It is
noted that the index may also be stored with a mixture of central
and remote storage, as desired. In addition, as indicated above, a
directory or summary index for the resulting index may be generated
and stored centrally, if desired. It is further noted that the
summary index may be stored in any other desired fashion, for
example, it may be distributed and stored on a number of client
systems.
[0095] FIG. 6A is a block diagram for a server system 104 according
to the present invention, including a control system 304, a
workload database 308, and a database of capability vectors 620.
The workload database 308 includes a variety of sets of workload
projects WL1, WL2 . . . WLN. For each workload project, there may
be multiple workload units. For example, workload project WL1
includes workload units WL11, WL12 . . . WL1N, as represented by
elements 640, 642 . . . 644, respectively. Similarly, workload
project WL2 includes workload units WL21, WL22 . . . WL2N, as
represented by elements 646, 648 . . . 650, respectively workload
project WL3 includes workload units WL31, WL32 . . . WL3N, as
represented by elements 652, 654 . . . 656, respectively.
[0096] It may be expected that different workload projects WL1, WL2
. . . WLN within the workload database 308 may require widely
varying processing requirements. Thus, in order to better direct
resources to workload projects, the server system may access
various system vectors when a client system signs up to provide
processing time and other system or device capabilities to the
server system. This capability scheduling helps facilitate project
operation and completion. In this respect, the capability vector
database 620 keeps track of any desired feature of client systems
or devices in capability vectors CBV1, CBV2 . . . CBVN, represented
by elements 628, 630 . . . 632, respectively. These capability
vectors may then be utilized by the control system 304 through line
626 to capability balance workloads.
[0097] This capability scheduling according to the present
invention, therefore, allows for the efficient management of the
distributed processing system of the present invention. This
capability scheduling and distribution will help maximize
throughput, deliver timely responses for sensitive workloads,
calculate redundancy factors when necessary, and in general, help
optimize the distributed processing computing system of the present
invention. The following TABLE 1 provides lists of capability
vectors or factors that may be utilized. It is noted that this list
is an example list, and any number of vectors or factors may be
identified and utilized, as desired.
1TABLE 1 Example Client Capability Vectors or Factors 1. BIOS
Support: a. BIOS Type (brand) b. ACPI c. S1, S2, S3, and S4
sleep/wake states d. D1, D2 and D3 ACPI device states e. Remote
Wake Up Via Modem f. Remote Wake Up Via Network g. CPU Clock
control h. Thermal Management control i. Docked/Undocked state
control j. APM 1.2 support k. Hotkey support l. Resume on Alarm,
Modem Ring m. Password Protected Resume from and LAN Suspend n.
Full-On power mode o. APM/Hardware Doze mode p. Stand-by mode q.
Suspend to DRAM mode r. Video Logic Power Down s. HDD, FDD and FDC
Power Down t. Sound Chip Power Down u. Super I/O Chip Power Down 2.
CPU Support: a. CPU Type (brand) b. MMX instruction set c. SIMD
instruction set d. WNI instruction set e. 3DNow instruction set f.
Other processor dependent g. Raw integer performance instruction
set(s) h. Raw FPU performance i. CPU L1 data cache size j. CPU L1
instruction cache size k. CPU L2 cache size l. CPU speed (MHz/GHz .
. . ) m. System bus (MHz/GHz . . . ) speed supported n. Processor
Serial Number o. CPUID 3. Graphic Support a. Graphics type (brand)
b. # of graphics engines c. Memory capacity d. OpenGL support e.
Direct3D/DirectX support f. Color depth supported g. MPEG 1/II
decode assist h. MPEG1/II encode assist i. OS support j. Rendering
type(s) supported k. Single-Pass Multitexturing support l. True
Color Rendering m. Triangle Setup Engine n. Texture Cache o.
Bilinear/Trilinear Filtering p. Anti-aliasing support q. Texture
Compositing r. Texture Decompression s. Perspectively Correct
Texture Mapping t. Mip-Mapping u. Z-buffering and Double-buffering
support v. Bump mapping w. Fog effects x. Texture lighting y. Video
texture support z. Reflection support aa. Shadows support 4.
Storage Support a. Storage Type (brand) b. Storage Type (fixed,
removable, c. Total storage capacity etc.) d. Free space e.
Throughput speed f. Seek time g. User dedicated space for current
workload h. SMART capable 5. System a. System Type (brand) b.
System form factor (desktop, portable, workstation, server, etc.)
6. Communications Support a. Type of Connection (brand of ISP) b.
Type of Connection Device (brand c. Hardware device capabilities of
hardware) d. Speed of connection e. Latency of connection f. Round
trip packet time of g. Number of hops on connection type connection
h. Automatic connection support i. Dial-up only (yes/no) (yes/no)
j. Broadband type (brand) k. Broadband connection type
(DSL/Sat./Cable/T1/Intranet/etc.) 7. Memory a. Type of memory error
correction (none, ECC, etc.) b. Type of memory supported (EDO, c.
Amount of total memory SDRAM, RDRAM, etc.) d. Amount of free memory
e. Current virtual memory size f. Total available virtual memory
size 8. Operating System a. Type of operating system (brand) b.
Version of operating system c. Health of operating system 9. System
application software a. Type of software loaded and/or operating on
system b. Version of software c. Software features enabled/disabled
d. Health of software operation
[0098] FIG. 6B is a functional block diagram for capabilities
determination and scheduling operation 600 for workloads in a
distributed processing system according to the present invention.
Initially, various vectors are identified for which capability
information is desired in the "identify client system capability
vectors" block 602. Following line 612, the server systems 104 then
capability balances workloads among client systems 108, 110 and 112
based upon the capability vectors in the "capability scheduling
workloads based on vectors" block 604. Then the capabilities
scheduled workloads are sent to the client systems 104 for
processing in the "send capability scheduled workloads" block
606.
[0099] This capability scheduling and management based upon system
related vectors allows for efficient use of resources. For example,
utilizing the operating system or software vectors, workloads may
be scheduled or managed so that desired hardware and software
configurations are utilized. This scheduling based upon software
vectors may be helpful because different software versions often
have different capabilities. For example, various additional
features and services are included in MICROSOFT WINDOWS '98 as
compared with MICROSOFT WINDOWS '95. Any one of these additional
functions or services may be desired for a particular workload that
is to be hosted on a particular client system device. Software and
operating system vectors also allow for customers to select a wide
variety of software configurations on which the customers may
desire a particular workload to be run. These varied software
configurations may be helpful, for example, where software testing
is desired. Thus, the distributed processing system of the present
invention may be utilized to test new software, data files, Java
programs or other software on a wide variety of hardware platforms,
software platforms and software versions. For example, a Java
program may be tested on a wide proliferation of JREs (Java Runtime
Engines) associated with a wide variety of operating systems and
machine types, such as personal computers, handheld devices,
etc.
[0100] From the customer system perspective, the capability
management and the capability database, as well as information
concerning users of the distributed devices, provide a vehicle
through which a customer may select particular hardware, software,
user or other configurations, in which the customer is interested.
In other words, utilizing the massively parallel distributed
processing system of the present invention, a wide variety of
selectable distributed device attributes, including information
concerning users of the distributed devices, may be provided to a
customer with respect to any project, advertising, or other
information or activity a customer may have to be processed or
distributed.
[0101] For example, a customer may desire to advertise certain
goods or services to distributed devices that have certain
attributes, such as particular device capabilities or particular
characteristics for users of those distributed devices. Based upon
selected attributes, a set of distributed devices may be identified
for receipt of advertising messages. These messages may be
displayed to a user of the distributed device through a browser,
the client agent, or any other software that is executing either
directly or remotely on the distributed device. Thus, a customer
may target particular machine specific device or user attributes
for particular advertising messages. For example, users with
particular demographic information may be targeted for particular
advertisements. As another example, the client agent running on
client systems that are personal computers may determine systems
that are suffering from numerous page faults (i.e., through
tracking operating system health features such as the number of
page faults). High numbers of page faults are an indication of low
memory. Thus, memory manufactures could target such systems for
memory upgrade banners or advertisements.
[0102] Still further, if a customer desires to run a workload on
specific device types, specific hardware platforms, specific
operating systems, etc., the customer may then select these
features and thereby select a subset of the distributed client
systems on which to send a project workload. Such a project would
be, for example, if a customer wanted to run a first set of
simulations on personal computers with AMD ATHLON microprocessors
and a second set of simulations on personal computers with INTEL
PENTIUM III microprocessors. Alternatively, if a customer is not
interested in particular configurations for the project, the
customer may simply request any random number of distributed
devices to process its project workloads.
[0103] Customer pricing levels for distributed processing may then
be tied, if desired, to the level of specificity desired by a
particular customer. For example, a customer may contract for a
block of 10,000 random distributed devices for a base amount. The
customer may later decide for an additional or different price to
utilize one or more capability vectors in selecting a number of
devices for processing its project. Further, a customer may request
that a number of distributed devices be dedicated solely to
processing its project workloads. In short, once device attributes,
including device capabilities and user information, are identified,
according to the present invention, any number of customer
offerings may be made based upon the device attributes for the
connected distributed devices. It is noted that to facilitate use
of the device capabilities and user information, capability vectors
and user information may be stored and organized in a database, as
discussed above.
[0104] Referring now to FIG. 12A, a block diagram depicts a
distributed processing system 1200 that allows customers to select
client system attributes, such as device capabilities and user
characteristics, according to the present invention. In this
embodiment, the network 102 is depicted as the Internet to which
server systems 104, customer 152A, customer 152B, and client
systems 1202A, 1202B . . . 1202C are connected. These systems are
connected through communication links 114, 119A, 119B, 1204A, 1204B
. . . 1204C, respectively. As noted above, these communication
links may include any of a wide variety of devices and/or
communication techniques for allowing a system to interface with
other connected systems.
[0105] As shown in FIG. 12A, and as discussed above, the customers
152A and 152B may desire to send information or projects, such as
advertisements (ADV) 1206A and 1206B and/or projects (PROJ) 1208A
and 1208B, to groups of client systems that have particular or
selected capabilities. The number of different groups of client
systems is as varied as the capability and user data available for
those client systems. The client systems 1202A represent client
systems that include a first set (Set 1) of desired attributes. The
client systems 1202B represent client systems that include a second
set (Set 2) of desired attributes. And the client systems 1202C
represent client systems that include a Nth set (Set N) of desired
attributes. Once attributes are selected, the client systems with
those attributes may be accessed as desired by customers 152A and
152B. For example, customer 152A may send its advertisement to
client systems 1202B. Customer 152B may send its advertisement to
client systems 1202A. The project 1208A from customer 152A may be
processed by client systems 1202C. And the project 1208B from
customer 152B may be processed by client systems 1202B. It is
noted, therefore, that any combination of desired attributes, such
as device capabilities and user characteristics, may be identified
and utilized to satisfy customer objectives, whether those
objectives be advertising, project processing, or some other
desired objective.
[0106] FIG. 12B is a block flow diagram for client system attribute
selection, according to the present invention. In the embodiment
shown, process 1250 begins with the customer selecting desired
attributes in block 1252. Next, client systems with selected
attributes are accessed in block 1254. And, then in block 1256, the
customer objective, such as advertising or project, is processed by
the client system. Control of this process 1250 may be provided by
the server systems 104, if desired, such that the customer
interfaces with the server systems 104 to select device attributes
and then the servers systems 104 access the client systems.
Alternatively, the server systems 104 may simply provide the
customer with a list of contact information (e.g., IP addresses)
for the client systems, so that the customer may directly access
the client system, for example, in providing advertisements to the
users of the client systems. It is further noted that other control
techniques may also be used to identify and access client systems
with particular desired device capabilities, user characteristics,
or other device attributes, according to the client system
attribute selection method of the present invention.
[0107] FIG. 7A is a block diagram for a network 102 according to
the present invention, including example network sites 106A and
106B on which site testing is to be conducted, such as load testing
and/or quality-of-service (QoS) testing. FIG. 7A is similar to FIG.
1A except that other systems 106 in FIG. 1A has been represented in
the embodiment of FIG. 7A with network sites 106A and 106B.
Communication line 116A between the network 102 and the network
site 106A represents a interaction by one client system 108, 110
and 112. Communication lines 116B, 116C and 116D represent
interactions by more than one client system 108, 110 and 112.
[0108] Site testing is typically desired to determine how a site or
connected service performs under any desired set of test
circumstances. With the distributed processing system of the
present invention, site performance testing may be conducted using
any number of real client systems 108, 110 and 112, rather than
simulated activity that is currently available. Several tests that
are commonly desired are site load tests and quality of service
(QoS) tests. Quality of service (QoS) testing refers to testing a
user's experience accessing a network site under normal usability
situations. Load testing refers to testing what a particular
network site's infrastructure can handle in user interactions. An
extreme version of load testing is a denial-of-service attack,
where a system or group of systems intentionally attempt to
overload and shut-down a network site. Advantageously, the current
invention will have actual systems testing network web sites, as
opposed to simulated tests for which others in the industry are
capable.
[0109] Network site 106B and the multiple interactions represented
by communication lines 116A, 116B and 116C are intended to
represent a load testing environment. Network site 106A and the
single interaction 116A is indicative of a user interaction or QoS
testing environment. It is noted that load testing, QoS testing and
any other site testing may be conducted with any number of
interactions from client systems desired, and the timing of those
interactions may be manipulated and controlled to achieve any
desired testing parameters. It is further noted that periodically
new load and breakdown statistics will be provided for capacity
planning.
[0110] FIG. 7B is a functional block diagram for a site-testing
operation 700 according to the present invention. Initially, client
systems 108, 110 and 112 receive workloads that identify testing
procedures and parameters in the "clients receive testing workload"
block 702. Following line 714, the client systems 108, 110 and 112
access the site being tested and perform the testing in block
"clients interact with other systems" block 704. Next, following
lines 716 and 718, the client systems 108, 110 and 112 complete the
site testing workload tasks, get the results ready for
transmission, and send those results back to the system server 104
in "clients complete testing workload" block 706 and "site testing
results sent to server system" block 708. Control passes along line
720 to "site testing results compiled for use" block 510 where the
server system formats and/or compiles the results for use by the
network site. For example, the site testing results may be utilized
determining modifications that need to be made to the network site
to handle peek volume activities.
[0111] FIG. 8 is a block diagram for a distributed processing
system 800 for a data back-up system application, according to the
present invention. As stated above with respect to FIG. 1A, the
network 102 may be a wide variety of networks, including an
intranet network. Intranet networks, such as internal networks set
up by corporations, are particularly suited for this application
because the systems holding the data being backed-up would be owned
by the same entity owning other systems with excess data storage
capabilities. In this way, security would not be as great of an
issue and the client system types could be better controlled. It is
noted, however, that this data back-up application would be equally
applicable to other networks, such as for computer systems
connected through the Internet.
[0112] Referring back to FIG. 8, client systems 108, 110 . . . 112
are shown each having a back-up data blocks 804, 806 . . . 808.
Customer systems 152 is shown as having data 802, which is desired
to be backed-up with the distributed back-up system 800. The server
systems 104 manage the flow of data from the data 802 and the
client systems that have extra storage space represented by back-up
data blocks 804, 806 . . . 808. In operation, the server systems
104 identifies client system storage capabilities. With this
information, the server systems 104 can receive data for back-up
from any system on the network 102. It is noted, and as indicated
with respect to FIG. 1A, the client systems 108, 110 . . . 112 and
the customer systems 152 may communicate directly with each other
in peer-to-peer type communications.
[0113] The servers systems 104 may also manage the storage and
transfer of data so that the data will be readily retrievable once
backed-up and stored on the client systems 108, 110 . . . 112. If
desired, an summary index or directory of the backed-up data may be
stored centrally on the server systems 104, or may be stored
remotely on the client systems 108, 110 . . . 112. It is also noted
that the server systems 104 may also distribute data back-up
workloads so that each portion of the data 802 is stored
redundantly on at least two of the client systems 108, 110 . . .
112. This redundancy provides added security should any one or more
client systems suddenly cease to be operational.
[0114] Looking now to FIG. 9, a block diagram is depicted of an
alternative representation of an interconnection fabric for a
distributed processing system environment 100, according to the
present invention. In this diagram and as described above, the
network environment may be the Internet, an internal company
intranet, a local area network (LAN), a wide area network (WAN), a
wireless network, a home network, or any other system that connects
together multiple systems and devices. In addition, the server
systems and clients systems may be interconnected by a variety of
possible connection interfaces, for example, Ethernet connections,
wireless connections, ISDN connections, DSL connections, modem
dial-up connections, cable modem connections, direct T1 or T3
connections, fiber optic connections, routers, portal computers, as
well as any other network or communication connection. It is noted,
therefore, as discussed with respect to other embodiments such as
the embodiment of FIG. 1A, that systems may be coupled into an
interconnected fabric in any of a variety of ways and
communications can potentially occur directly or indirectly between
any of the systems coupled into the fabric, as would be understood
by those of skill in the art.
[0115] Within this environment, as depicted in FIG. 9, server
systems 104 are interconnected with any number of client systems,
for example, client systems 108A, 108B, 108C, 108D, 108E, 108F,
108G, 108H, 108I, 108J, 108K and 108L. In addition, these client
systems may also include idle client systems 902A, 902B, and 902C,
as discussed further below. Furthermore, these client systems may
include client system 904A with a component A, client system 904B
with a component B, and client system 904C with a component C. It
is also noted that the interconnection fabric may include any
number of devices that are not client systems, in that they
themselves are not providing components or processing capabilities
for the distributed processing system of the present invention.
Nevertheless, these devices may be considered part of the system
because they may relay, interpret, process or otherwise transmit or
receive information from or to client systems that are part of the
distributed processing system. Aggregation of component level
resources, according to the present invention, will now be
discussed. As described above, the capabilities of client systems
are determined for purposes of allocating, scheduling and managing
distributed processing workloads. In other words, each of the
client systems may be made up of many individual subsystems with
various capabilities. In some cases, it may occur that particular
components on different machines may provide added value if
combined or aggregated. Thus, utilizing subsystem or component
level resources from a heterogeneous group of devices may be the
most efficient or otherwise advantageous way of taking advantage of
these resources to complete various desired tasks.
[0116] Referring now more particularly to FIG. 9, the client
systems 904A, 904B and 904C may have component A, component B and
component C, respectively, that are better utilized in combination.
For example, client system 904A may have a fast processor, a
high-speed network connection, but little available storage space.
Client system 904B may have large amounts of available free storage
space but little processing power. Client system 904C may also have
a fast processor, but relatively little available storage space. In
this example, a workload that requires both a large storage
capacity and a fast processor may be efficiently completed by
dedicating component level resources to various parts of the
workload from different machines. Thus, the workload may be managed
by having client systems 904A and 904C processing data stored on
and transmitted from client system 904B. Once clients systems 904A
and 904C process data, this resulting data may then be transmitted
back to client system 904B for aggregation and eventual
transmission back to the server systems 104. The client system
904B, therefore, essentially acts as a server for a workload
subset, sending out portions of a subset workload, receiving back
the processed data, and aggregating the data to build a completed
workload subset.
[0117] It is noted that any number of different components from
different client systems may be aggregated, as desired. For
example, for wireless devices, DSP processing and storage
components could be aggregated with components from other client
systems. For display devices, graphics rendering power could be
aggregated. For relatively dumb machines, such as connected
household appliances, vending machines, etc., slow-speed processing
components could be aggregated. In short, an appropriate workload
may include instructions to numerous client systems that will
enable collaboration and aggregation of component level resources.
Such instructions may include things, such as, where to receive
input, where to send output, and ultimately which client systems
return final results.
[0118] It is further noted that the control instructions may be
de-centralized as well. In other words, as indicated above, client
systems may communicate directly with each other, for example, in a
peer-to-peer fashion. In this way, workload communications may
occur directly between client systems, and workload control and
management may occur through the client system agents located on
client systems.
[0119] Still referring to FIG. 9, idle system determination will
now be discussed. As stated above, client system capabilities are
determined and utilized within the distributed processing system of
the present invention. The more idle any particular client system,
the more processing it is arguably able to accomplish, and the more
incentives it is likely to receive. In other words, the client
system capabilities may be utilized more often and more intensely
if the client system is more idle. As such, it is advantageous to
identify idle client systems and allocate them to more processor
and time sensitive tasks. By identifying these idle client systems,
resources available on the network at any given time may be more
fully utilized, and otherwise idle resources may be utilized for
highly intensive, real-time activities that would otherwise require
dedicated devices. Examples of such real-time activities include
data caching, indexing, etc. In FIG. 9, idle client systems are
designated as 902A, 902B and 902C.
[0120] Identifying idle resources may be determined in any of a
variety of ways. It is possible, for example, to simply look at
whether a machine is not being used or has low processor
utilization at any given time. This simple determination, however,
may not yield an accurate picture of how idle a client system may
or may not be over a given time period. More particularly,
discovery methods may be implemented to identify the activity of a
variety of client system components and subsystems. For example,
subsystems may be monitored, such as network activity, device
output activity, user input, processing activity, executing task
monitoring, or mode of operation parameters (e.g., mobile or power
management modes, stationary or powered mode). In addition, any
number of other device vectors may be monitored or analyzed to
determine the true usage and idleness of a client system.
[0121] The following TABLE 2 provides a list of idleness vectors or
factors that may be utilized in determining the level of device
usage or idleness. In particular, TABLE 2 provides two primary
categories of activities to monitor or analyze for determination of
how idle a client system may or may not be. These activities are
user activity and device activity. By monitoring, analyzing and
tracking these client system elements and activities over time, a
better determination of device usage and idleness may be made. It
is noted that the list provided in TABLE 2 is an example list, and
any number of categories, vectors or factors may be identified and
utilized, as desired, according to the present invention.
2TABLE 2 Example Client Idleness Vectors or Factors 1. User
Activity (e.g., monitor input a. keyboard input activities, monitor
output activities, monitor time elapsed since last input event and
between input events, etc.) b. mouse input c. microphone/voice
input d. tablet input e. pen input f. touch screen input g.
joystick input h. gamepad input i. video output j. printer output
k. any other user activity that could be utilized to classify if a
device is idle 2. Device Activity (e.g., monitor a. power state
(e.g., time since last utilization levels, monitor time elapsed
power state change event) since last device activity, monitor time
between changes in device utilization levels, etc.) b. mobility
state (e.g., time since c. screen saver activity or trigger (e.g.,
device last in mobile state) time elapsed since screensaver
activity or trigger) d. screen output (e.g., time elapsed e.
network or communication packets since last screen output, paint
event sent or received (e.g., time elapsed or pixel change) since
last network or communications activity) f. storage device activity
(e.g., time g. processor, DSP, microcontroller, elapsed since last
storage device embedded device, or other activity, such as hard
drives, flash processor activity (e.g., time memory cards,
removable drives, elapsed since last processor CD drives, DVD
drives, etc.) activity) h. processor, DSP, microcontroller, i.
tasks or processes executing (e.g., embedded device, or other time
elapsed since change in processing device utilization (e.g., number
of tasks or processes change in utilization levels) executing) j.
task or process device utilization k. any other device activity
that could (e.g., time since change in task or be used to classify
if a device is idle process device utilization)
[0122] As a further example of the usefulness of this
determination, reference is made back to FIG. 9. Server systems 104
may have, for example, a large, intensive task that it would like
to place on these idle devices. After using a number of the vectors
in TABLE 2 to determine the utilization level for client systems,
the server systems 104 determines that client systems 902A, 902B
and 902C are idle and capable of handling significant time
sensitive processing tasks. For example, idle client systems 902A,
902B and 902C may be personal computers that can act as a local
internet cache for other connected devices, such as some of the
other client systems depicted in FIG. 9, that are interested in a
data type that benefits from a local network cache. Thus, data or
content may be transmitted from a remote network site to the idle
machines 902A, 902B and 902C. These idle devices 902A, 902B and
902C may then re-transmit this same data or content to other
connected devices also interested in the data or content.
[0123] One example for such network caching is Internet video or
multimedia broadcast events that are desired to be viewed or
received by a very large number of geographically close connected
devices at about the same time. In order to meet the demand of
these connected devices, web sites broadcasting an event have to be
able to handle a huge increase in network traffic over a short
period of time. By locally caching the transmission to idle client
systems, a web site can reduce the direct demand on its own
resources. This is so because other connected devices may receive a
re-transmitted broadcast, although delayed, from the idle client
system. It is noted that according to the present invention idle
client systems 902A, 902B and 902C may work independently or in
combination. Even though idle client systems are suited for
providing the caching function, it is also noted that that network
caching may be accomplished using one or more client systems
regardless of their respective levels of idleness.
[0124] FIG. 10 is a more detailed block diagram for a client system
agent 270 installed on a client system, according to the present
invention. This diagram includes a security subsystem 1010, a
capabilities subsystem 1006, a workload processor 1004, a user
interface 1002, and a project management and agent control
subsystem 1008. The various components and subsystems may
communicate with each other, for example, through lines 1012, 1014,
1016, 1018 and 1020. Externally, the client system agent 270 may
communicate through its security subsystem 1010 with the other
components within the client system and ultimately to other devices
connected into the network fabric. It is noted that configuration
of the client system agent and its operation, both internal and
external, may be selected and designed, as desired.
[0125] As depicted, the capabilities subsystem 1006 includes an
idle system monitor 1022, as described above, that monitors and
analyzes user and device activities associated with the client
system to determine the level of activity or idleness for the
client system. The information determined by this idle system
monitor 1022 may then be communicated externally, for example,
through the security subsystem 1010 to the server systems 104. The
server systems 104 may then store and analyze system idleness data
from across the distributed processing system. This idleness data
may become part of the capabilities database that is utilized to
allocate and manage workloads and processing system resources.
[0126] Still referring to FIG. 10, the workload processor 1004
includes a machine entry generation subsystem 1024. As described
above, the workload processor 1004 may send completed workloads
back to server systems 104 to generate sweepstakes entries for the
host client system. In this way, when the incentive is a
sweepstakes, the client system may generate entries by completing
workloads. The machine entry generation subsystem 1024 refers to
this entry generation through workload completion. As discussed
above, the workload processed to generate entries may be a project
workload, an entry workload, or any other workload, as desired.
[0127] FIGS. 11A and 11B provide more detailed flow diagrams of
process embodiments for machine generated sweepstakes entries
through processing of entry workloads, according to the present
invention.
[0128] Looking first to FIG. 11A, an entry workload process flow
1100 is depicted that provides machine generated sweepstakes
entries. Process moves from start block 1102 to block 1104 in which
entry workloads are loaded on client systems. Next, process flows
to block 1106 which represents a periodic timer or other timing
control for entry workload processing. After this timing control,
the client system executes or processes the entry workload in block
1108. In block 1110, a sweepstakes entry is thereby generated and
returned to the server system 104 based upon the completion of this
entry workload. Process control then may proceed back to the
periodic timing block 1106, where timing control determines when
the entry workload is next processed. The completed workload
represents the machine generated sweepstakes entry.
[0129] FIG. 11B is an alternative entry workload process flow 1150.
The process flow 1150 is similar to the process flow 1100 except
that the entry workload is sent to the client system each time it
is to be run. Process starts in block 1102 and passes to the
periodic timer block 1106, in which the process is controlled. For
example, server systems 104 may determine when it is desirable for
the client systems to receive and process an entry workload. In
block 1104, the entry workload is sent to the client systems. As
with FIG. 11A, the client systems then execute the entry workload
in block 1108, and an entry is generated and returned to the remote
server systems 104 in block 1110. The process then proceeds back to
the periodic timer 1106 until it is determined that another entry
workload should be processed. The primary difference between
process 1150 and process 1100 is that process 1150 is depicting an
entry workload that is transmitted to the client system each time
it is to be run.
[0130] One example utilizing the process 1150 or the process 1100
is for servers systems 104 to query the client systems for entry
workload processing at regular time intervals. If a distributed
device returns a completed entry workload back within a selected
period of time from the distribution of the entry workload, the
server system may conclude that the distributed device should
receive an entry because the distributed device is providing
resources to the distributed processing system. In this way, the
server systems 104 may determine at regular intervals whether a
given client system is working on project workloads for the
distributed processing system. Alternatively, the client system
agent may locally control the workload processing and may, for
example, cause the client system to process and generate entries at
regular time intervals. It is noted that non-regular and varying
time intervals may also be utilized and that combinations of remote
and local control may also be utilized, as desired.
[0131] The timing of when a client system processes the entry
workload, therefore, may be determined locally by the client system
agent or remotely, for example, through commands sent by the server
systems 104. In addition, periodic timing control may also be
accomplished through various combinations of control routines
residing locally and remotely. It is further noted that any number
of different variations may be utilized to provide machine
generated entries to a sweepstakes, according to the present
invention. Thus, a client system may generate sweepstakes entries
in any of a variety of ways and still have machine generated
sweepstakes entries, according to the present invention.
[0132] FIGS. 13A and 13B describe a data conversion application
1300 for a massively parallel distributed network according the
present invention. In particular, FIG. 13A is a block diagram of a
distributed processing system that provides data conversion
services, according to the present invention. And FIG. 13B is a
block flow diagram for data conversion services within a
distributed processing system, according to the present
invention.
[0133] Converting file types, web pages, graphics images, etc.,
between device types can be a highly intensive processing task.
Example devices that often need converted data are wireless
devices, such as pagers and cell phones, that request Internet web
page information from their respective device servers. The device
server, instead of incurring the overhead of reformatting the
requested data for the wireless devices, may instead distribute the
requested page or data address, the device type information of the
requesting device, and return address for the reformatted data.
According to the present invention, the data conversion,
translation or processing may be performed by a client system of
the distributed processing system of the present invention. The
resulting data may then be returned or provided to the original
requesting device. In addition to data formatting for cell phones,
language conversion, text translation and media translation
services, or any other desired data conversion can also be hosted
for a customer through the distributed processing system of the
present invention.
[0134] It is noted that the data conversion operation contemplated
by the present invention is not limited to any particular
requesting device, any particular service provider, any particular
type of data to be processed, any particular type of resulting
processed data, or any particular data source. Thus, the data
processed may include voice, text, application, image, source code,
or any other data type or combination of data types, and the
resulting processed data may also include voice, text, application,
image, or any other data type or combination of data types.
According to the present invention, the distributed processing
system is utilized to process any data that is desired by a
requesting device and that must be converted or processed before
being provided to the requesting device. For example, an end-user
devices connected to the Internet, such as personal computers, may
sign up for data conversion services through the server system so
that the end-user device may request data conversion of any desired
data, file, web site content, etc. Language translations and data
formatting for connected wireless are just two examples of such
applications for the present invention.
[0135] Looking now to the embodiment of FIG. 13A, the network 102
is depicted as the Internet, and the requesting device is one or
more wireless devices 1306 connected to the Internet 102 through
communication links 1308 and to the wireless device server systems
1304 through communication link 1309. The data to be converted,
translated or otherwise processed is represented by block 1302 and
may be, for example, content from an Internet web site that is
connected to the Internet through communication link 1312. Also, as
shown in FIG. 13A, a massively parallel distributed network (MPDN)
server 104 is connected to the Internet 102 through communication
link 114. The wireless device server systems 1304, or any other
connected system that desires to off-load data conversion
processing requirements (e.g., web site content servers), are
connected to the Internet 102 through communication links 1310 and
to the MPDN server 104 through communication links 1311. Any number
of client systems 108, 110 . . . 112 may also be connected to the
Internet 102, through communications links 118, 120 . . . 122,
respectively. As also stated above, any of the connected devices
may communicate with each other in any of a wide variety of
communication techniques (e.g., wireless, electrical, digital,
analog, light-based, etc.) and protocols (e.g., static or dynamic
IP addresses), and through any number of other devices, as would be
understood by one of skill in the art.
[0136] In the application contemplated by FIG. 13A, the wireless
devices 1306 at times request data, for example, images or text
from a web site, that must be converted, translated or otherwise
processed by wireless device server systems 1304 before it can be
transmitted to, and displayed on, a requesting wireless device.
Instead of converting the information, the wireless device servers
systems 1304 may request that the MPDN server 104 accomplish the
data conversion or translation. The device server systems 1304 may
then provide to the MPDN server 104 any pertinent information, such
as information concerning the requesting device, the nature of the
data requested, and the processing needed for the data. The MPDN
server 104 may then utilize one or more of the client systems 108,
110 . . . 112 to process the data from block 1302 for transmission
to the requesting device. In this way, the wireless device server
systems 1304 may off-load burdensome and process-intensive
conversion tasks to the distributed processing system of the
present invention.
[0137] It is noted the transmission of processed data to the
requesting wireless device 1306 may occur in a variety of ways. For
example, the processed data may be transmitted from a client system
108 to the server 104, then to the wireless device server 1304 and
finally to the wireless devices 1306. Alternatively, the processed
data may be transmitted from a client system to the wireless device
server 1304, and then to the wireless devices 1306. Still further,
the processed data may be transmitted directly from a client system
to the wireless devices.
[0138] FIG. 13B provides a basic flow diagram for an embodiment of
a data conversion process 1350 according to the present invention.
In block 1352, a device, such as wireless devices 1306, requests
unconverted, non-translated or non-processed data. In block 1354, a
server for the device, such as wireless device server systems 1304,
processes the data request and contacts the MPDN server 104. In
addition, the content provider or server for the requested data,
such as a web site content server, may contact the MPDN server 104.
The wireless device server systems 1304 provide all pertinent
information to the MPDN server 104, such as the type of calling
device, its identification, the relevant data requested, and the
conversion to take place. The MPDN server 104 then distributes the
data and information concerning the requesting device to one or
more client systems, such as client systems 108, 110 . . . 112, in
block 1356. The one or more client systems then convert, translate
or otherwise process the data in block 1358. The converted,
translated or processed data is then provided to the requesting
device in block 1360. Again, in this way, the device servers may
provide a wide range of information without having to provide
itself the processing power to accomplish the conversion,
translation or processing that is required to transmit or display
the data on a requesting device.
[0139] As shown in FIG. 13B, the device server or the content
server 1304 may communicate data and other pertinent information
for a conversion directly to the client systems. For example, the
MPDN server 104 may provide access to a group of client systems for
data conversion purposes for given periods time (e.g., monthly
client group allocations), or may provide identities of groups of
client systems that may be used at the time a conversion is needed.
Once the identity and allocation of client systems to a particular
device server or content server is made, the device server or
content server may communicate directly with the client systems. In
addition, the device server or content server may provide directly
to a requesting device the identity of the one or more client
systems accomplishing the data conversion. As shown in FIG. 13B,
the requesting device, therefore, may communicate directly with the
client system or systems to provide pertinent information
concerning the data conversion requested. The client system may
then, for example, directly download the desired content and
perform the desired data conversion. It is further noted that in
addition to the embodiments described above with respect to FIGS.
13A and 13B, other methods for requesting, processing and providing
data to and from the requesting device may be implemented with
distributed processing system of the present invention, such as
caching processed data for later transmission.
[0140] FIGS. 14A and 14B depict example block diagrams of file
distribution and data sharing through the network fabric, according
to the present invention. In particular, FIG. 14A depicts an
Internet data file distribution system 1400 that relies upon client
systems to provide local data distribution. FIG. 14B depicts a data
file distribution system 1450 that allows for data sharing and
rapid transmission of a project or data files through the
distributed processing system.
[0141] Looking now to FIG. 14A, a block diagram is depicted of a
distributed processing system 1400 that provides data transmission
caching or other local distribution, according to the present
invention. In the embodiment of FIG. 14A, server systems 104 are
connected through communication link 114 to the Internet back bone
1402. The Internet back bone 1402 represents the very high speed
connections that carry data long distances, for example, T3 or
fiber optic lines that carry Internet data across the United
States. A web site 1404 is connected to the Internet back bone 1402
through communication link 1406, which represents a geographically
addition, the device server or content server may provide directly
to a requesting device the identity of the one or more client
systems accomplishing the data conversion. As shown in FIG. 13B,
the requesting device, therefore, may communicate directly with the
client system or systems to provide pertinent information
concerning the data conversion requested. The client system may
then, for example, directly download the desired content and
perform the desired data conversion. It is further noted that in
addition to the embodiments described above with respect to FIGS.
13A and 13B, other methods for requesting, processing and providing
data to and from the requesting device may be implemented with
distributed processing system of the present invention, such as
caching processed data for later transmission.
[0142] FIGS. 14A and 14B depict example block diagrams of file
distribution and data sharing through the network fabric, according
to the present invention. In particular, FIG. 14A depicts an
Internet data file distribution system 1400 that relies upon client
systems to provide local data distribution. FIG. 14B depicts a data
file distribution system 1450 that allows for data sharing and
rapid transmission of a project or data files through the
distributed processing system.
[0143] Looking now to FIG. 14A, a block diagram is depicted of a
distributed processing system 1400 that provides data transmission
caching or other local distribution, according to the present
invention. In the embodiment of FIG. 14A, server systems 104 are
connected through communication link 114 to the Internet back bone
1402. The Internet back bone 1402 represents the very high speed
connections that carry data long distances, for example, T3 or
fiber optic lines that carry Internet data across the United
States. A web site 1404 is connected to the Internet back bone 1402
through communication link 1406, which represents a geographically
communication links 1416A, 1416B and 1416C. It is noted that this
caching will be aided if the client and non-client devices
receiving the cached data are relatively short communication hops
from local distributor client device 1412E.
[0144] This data or network caching allows data to be streamed to
an end user level device, which may then pass the data on to other
end user devices. Thus, the downstream communications may be
limited, thereby taking the distribution burden off of the web
site. For example, web site 1404 may have a large streaming video
or multimedia file that is experiencing a heavy load from a given
set of network devices. This data file may be cached by a machine,
such as client device 1412E, that is below from a communication
link 1410. Then, other devices that are also below this
communication link 1410 may download the streaming video data from
the client device 1412E. This caching eliminates the need to
repeatedly send the same data through the same communication links
to requesting devices that are located below common communication
links. It is noted that the file and data distribution
possibilities for this peer file access, caching and data
transmission, according to the present invention, are wide and
varied and should not be seen as limited to the embodiment shown in
FIG. 14A.
[0145] FIG. 14B is a block diagram of a distributed processing
system 1450 that provides data distribution and data sharing,
according to the present invention. As with FIG. 9, FIG. 14B
depicts an alternative view of a network fabric that may
interconnect any of a wide variety of devices. In the embodiment
shown in FIG. 14B, server systems 104 are interconnected with any
number of client systems 108A, 108B, 108C, 108D, 108E, 108F, 108G
and 108H. Each of the connecting interconnects represents any of a
wide variety of communication links that may exist between devices
in the network fabric of the present invention. Each of the client
systems 108A, 108B, 108C, 108D, 108E, 108F, 108G and 108H include
shared data (SD) according to the present invention. Within this
interconnected fabric, block 1452 represents data or project
information that is desired to be distributed. The SD blocks within
each client system facilitates the distribution of this data or
project information.
[0146] A client agent, as discussed above, installed on the client
systems 108A, 108B, 108C, 108D, 108E, 108F, 108G and 108H includes
functionality that facilitates a number of services with respect to
data transmission and sharing. First, the client agent provides a
protected data storage area accessible to outside devices, which is
represented by the SD block within each client system in FIG. 14B.
This special storage space protects the device from outside devices
accessing other storage areas on the device while allowing data to
be shared and accessed by other devices and simultaneously used by
the local client agent.
[0147] These shared data (SD) blocks provide mechanisms that enable
a wide variety of possible interactions among the client systems
108A, 108B, 108C, 108D, 108E, 108F, 108G and 108H. For example, the
data sharing mechanism may provide a space for a cache of other
device addresses attached to the network for both communication
purposes as well as security purposes. The mechanism may also
provide a simple indexing system that is automatically re-indexed
when content is added or removed from the storage area. This
indexing system may provide a mechanism for other client agents to
perform discovery on the local client information and visa versa.
Through information stored within this shared data, the distributed
processing system of the present invention facilitates many
distributed file system applications such as distributed resume
posting, distributed caching, distributed advertisement serving,
etc. In addition to the above, the storage block (SD) within each
client system may include an interface for displaying or playing
data types (such as images, audio files, video files, etc.) stored
both locally and/or remotely on other client devices. This would
enable simple picture sharing, for example, between remote families
connected via the internet, as part of being a client system within
the distributed processing system of the present invention.
[0148] In the embodiment shown in FIG. 14B, data or project 1452 is
injected into the fabric through a connection to client system 108C
and server systems 104. These connections represent that the
information may pass first to servers systems 104, or may pass
first to a client system, such as client system 108C. It is noted
that there are other ways that the data may be injected into the
fabric. Once injected, the data 1452 may be transmitted throughout
the fabric through any of a wide variety of communications,
including client-to-client, server-to-client, client-to-server,
client-to-non-client, non-client-to-client communications, and/or
non-client-to-non-client communications. These communications may
be based upon a variety of mechanisms, such as polling mechanisms
and pre-assigned firewall ports. This technique provides a vehicle
that facilitates the distribution of information to a large number
of devices in a short period of time.
[0149] Applications for this data distribution are wide a varied.
For example, any important file that is time sensitive may be
propagated to a large number of client devices, non-client devices,
servers, or other connected devices, in a short amount of time.
This transmission may occur quickly and efficiently once the
information is injected into the distributed processing system of
the present invention. Example time sensitive data files are
anti-virus signature files, which when distributed through the
distributed processing system of the present invention, may be
transmitted through the network fabric faster than a new virus may
normally proliferate.
[0150] Another application for rapid propagation of files is
utilizing this technique for propagation of workloads. One example
is distributed resume or job searching. In such a system,
participating job seekers and participating employers may rapidly
search for one another. A job seeker may inject a job request or
search into the fabric that is then routed by each successive
device to other devices without the need for control from the
server systems 104. Similarly, an employer may inject candidate
criteria into the fabric that is then routed to successive devices.
The result is an extremely fast search and identification of
employers and candidates.
[0151] FIG. 15 is a block diagram of an alternative representation
for a distributed processing system 100, according to the present
invention. Server systems 104, database systems 1546 and web
interface 1554 are coupled together through communication links
1540, 1542 and 1544. The web interface 1554 includes clients
subsystem 1548, task developer subsystem 1550, and advertisers
subsystem 1552, and may include other subsystems as desired. The
database systems 1546 include workload (WL) information 308, client
capability vector information 620, and any other stored information
as desired. Server systems include various modules and subsystems,
including database interface 1532, web server 1536, task module and
work unit manager 1530, client statistics module 1534, advertising
manager 1538, task module version/phase control subsystem 1528,
sweepstakes engine 1524, server control subsystem 1526, and
communication interface 1522. It is noted that in the embodiment of
a distributed processing system 100 as depicted in of FIG. 15, the
three primary operations for the server systems 104, database
systems 1546 and web interface 1554 are directed to managing,
processing and providing an interface for client systems, customer
tasks, and customer advertising.
[0152] As discussed above, each client system includes a client
agent that operates on the client system and manages the workloads
and processes of the distributed processing system. As shown in
FIG. 15, each of the client agents 270A, 270B . . . 270C
communicates with the server systems 104 through communication
links 1516, 1518 . . . 1520, respectively. As discussed above, any
number of different techniques and architectures may be utilized to
provide these communication links. In the embodiment as shown in
FIG. 15 with respect to client agent 270A, each client agent
includes a base distributed processing system component 1506 and a
separate project or workload component 1504. As depicted, a
communication interface 1508, a core agent module 1502, and a user
interface 1510 make up the base distributed processing system
component 1506. The task module 1512 and the work unit 1514 make up
the separate project or workload component 1504. The task module
1512 operates on top of the core agent module 1502 to provide
processing of each project work unit 1514. It is noted that
different or additional modules, subsystems or components may be
included within the client agent, as desired. For example, a
personal computer screen saver component may be part of the base
distributed processing system component 1506 or the separate
project or workload component 1504.
[0153] Also as discussed above, security subsystems and interfaces
may be included to provide for secure interactions between the
various devices and systems of the distributed processing system
100. As depicted in FIG. 15, a security subsystem and interface
1560 is interconnected with the server systems 104, the database
systems 1546, the web interface 1554, and the client agents 270A,
270B . . . 270C. These interconnections are represented by lines
1566, 1564, 1562, and 1568, respectively. The security subsystem
and interface 1560 operates to secure the communications and
operations of the distributed processing system. This security
subsystem and interface 1560 also represents a variety of potential
security architectures, techniques and features that may be
utilized. This security may provide, for example, authentication of
devices when they send and receive transmissions, so that a sending
device verifies the authenticity of the receiving device and/or the
receiving device verifies the authenticity of the sending device.
In addition, this security may provide for encryption of
transmissions between the devices and systems of the distributed
processing system. The security subsystem and interface 1560 may
also be implemented in a variety of ways, including utilizing
security subsystems within each device or security measures shared
among multiple devices, so that security is provided for all
interactions of the devices within the distributed processing
system. In this way, for example, security measures may be set in
place to make sure that no unauthorized entry is made into the
programming or operations of any portion of the distributed
processing system including the client agents 270A, 270B . . .
270C.
[0154] In operation, client systems or end-users may utilize the
clients subsystem 1548 within the web interface 1554 to register,
set user preferences, check statistics, check sweepstakes entries,
or accomplish any other user interface option made available, as
desired. Advertising customers may utilize the advertisers
subsystem 1552 within the web interface 1554 to register, add or
modify banner or other advertisements, set up rules for serving
advertisements, check advertising statistics (e.g., click
statistics), or accomplish any other advertiser interface option
made available, as desired. Customers and their respective task or
project developers may utilize the task developer subsystem 1550 to
access information within database systems 1546 and modules within
the server systems 104, such as the version/phase control subsystem
1528, the task module and work unit manager 1530, and the workload
information 308. Customers may also check project results, add new
work units, check defect reports, or accomplish any other customer
or developer interface option made available, as desired.
[0155] Advantageously, the customer or developer may provide the
details of the project to be processed, including specific program
code and algorithms that will process the data, in addition to any
data to be processed. In the embodiment shown in FIG. 15, this
program code takes the form of a task module 1512 within the
workload, while the data takes the form of work unit 1514. These
two portions make up the project or workload component 1504 of each
client agent 270. For a given project, the task module 1512 will
likely remain relatively constant, except for version updates,
patches or phase modifications, while the work unit 1514 will
likely change each time processing of the data that it represents
is completed. The project or workload component 1504 runs in
conjunction with the base distributed processing system component
1506. When a different customer or project is started on a given
client system, the project or workload component 1504 will
typically be replaced, while the base distributed processing system
component 1506 will likely remain relatively constant, except for
version updates, patches or other modifications made for the
distributed processing system.
[0156] Information sent from the servers systems 104 to the client
agents 270A, 270B . . . 270C may include task modules, data for
work units, and advertising information. Information sent from the
client agents 270A, 270B . . . 270C to the server systems 104 may
include user information, system information and capabilities,
current task module version and phase information, and results. The
database systems 1546 may hold any relevant information desired,
such as workload information (WL) 208 and client capability vectors
(CV) 620. Examples of information that may be stored include user
information, client system information, client platform
information, task modules, phase control information, version
information, work units, data, results, advertiser information,
advertisement content, advertisement purchase information,
advertisement rules, or any other pertinent information.
[0157] Further modifications and alternative embodiments of this
invention will be apparent to those skilled in the art in view of
this description. It will be recognized, therefore, that the
present invention is not limited by these example arrangements.
Accordingly, this description is to be construed as illustrative
only and is for the purpose of teaching those skilled in the art
the manner of carrying out the invention. It is to be understood
that the forms of the invention herein shown and described are to
be taken as the presently preferred embodiments. Various changes
may be made in the shape, size and arrangement of parts. For
example, equivalent elements may be substituted for those
illustrated and described herein, and certain features of the
invention may be utilized independently of the use of other
features, all as would be apparent to one skilled in the art after
having the benefit of this description of the invention.
* * * * *