This application is a continuation-in-part application of the following applications: application Ser. No. 09/538,543 U.S. Pat. No. 7,003,547, entitled â€œDISTRIBUTED PARALLEL PROCESSING SYSTEM HAVING CAPABILITY-BASED INCENTIVES AND ASSOCIATED METHOD,â€ application Ser. No. 09/539,023 now abandoned, entitled â€œSWEEPSTAKES INCENTIVE MODEL AND ASSOCIATED SYSTEM,â€ application Ser. No. 09/539,448 now abandoned, entitled â€œCAPABILITY-BASED DISTRIBUTED PARALLEL PROCESING SYSTEM AND ASSOCIATED METHOD,â€ application Ser. No. 09/539,428 now abandoned, entitled â€œMETHOD OF MANAGING DISTRIBUTED WORKLOADS AND ASSOCIATED SYSTEM,â€ application Ser. No. 09/539,106 U.S. Pat. No. 6,891,802, entitled â€œNETWORK SITE TESTING METHOD AND ASSOCIATED SYSTEM,â€ application Ser. No. 09/538,542 U.S. Pat. No. 6,654,783, entitled â€œNETWORK SITE CONTENT INDEXING METHOD AND ASSOCIATED SYSTEM,â€ and application Ser. No. 09/539,107 now abandoned, entitled â€œDISTRIBUTED BACK-UP SYSTEM AND ASSOCIATED METHOD,â€ 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

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

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.

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.

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 2000â€”www.setiathome.ss1.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 10¹²floating point operations per second) running on about 1.8 million Internet connected machines.

Another example of a distributed processing technique was developed and implemented by Distributed.net (URL in March 2000â€”www.distributed.net) 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.

Entropia.com (URL in March 2000â€”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.

Another distributing processing web site is provided by Process Tree Network (URL in March 2000â€”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 â€œmicro-paymentsâ€ 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.

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 2000â€”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 2000â€”www.yahoo.com).

Significantly, these prior distributed processing projects have failed to fully utilize the capabilities of connected distributed devices.

SUMMARY OF THE INVENTION

The present invention provides a method for providing data sharing and filed distribution in 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.

In one embodiment, the present invention is a method of operating a distributed processing system to share data among distributed systems, including providing a first system, coupling the first system to a network that is configured to be coupled to distributed devices, operating an agent on the distributed devices to manage a workload on the distributed devices, allocating shared data storage on the distributed devices, storing information within the shared data storage, and allowing the agents operating on the distributed devices to access the information stored in the shared data storage on the distributed devices. More particularly, the information stored includes information to facilitate communication between multiple distributed devices, or information to facilitate processing of workloads by the distributed devices.

In another embodiment, the present invention is a distributed processing system with shared data capabilities, including a first system coupled to a network that is configured to be coupled to distributed devices, and a plurality of the distributed devices having agents that process distributed workloads and having information stored in shared data storage. The @ distributed devices allow agents on other distributed devices to access the shared data storage on the distributed devices. More particularly, the information stored includes information to facilitate rapid searching of employment information by either a person seeking employment or an employer seeking an employee.

In a further embodiment, the present invention is a method of operating a distributed processing system to distribute data among distributed systems, including providing a first system, coupling the first system to a network that is configured to be coupled to distributed devices, operating an agent on a plurality of the distributed devices to manage a workload on the distributed devices, and storing information on the distributed devices to facilitate distribution of data by the agents operating on the distributed devices. More particularly, the information stored includes information to facilitate distribution of time sensitive data, such as anti-virus signatures. The information stored may also be communication addresses of other distributed devices, the communication addresses allowing for rapid peer-to-peer communications. In addition, the method may include receiving a request for data transmission caching from a requesting device, and distributing workloads to at least one distributed device to accomplish the data transmission caching. The information stored includes cached data to be retransmitted to other distributed devices.

In another embodiment, the present invention is a distributed processing system providing data distribution services, including a first system coupled to a network that is configured to be coupled to distributed devices, and a plurality of the distributed devices having agents that process distributed workloads and having stored information that facilitates data distribution by the agents.

DESCRIPTION OF THE DRAWINGS

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.

FIG. 1A

is a block diagram for a distributed processing system having client capability and incentive features, according to the present invention.

FIG. 1B

is a block diagram for information flow among customer systems, server systems and client systems, according to the present invention.

FIG. 2A

is a block diagram for a client system, according to the present invention.

FIG. 2B

is a block diagram for processing elements within a client system, according to the present invention.

FIG. 2C

is a block diagram for a client system agent installed on a client system, according to the present invention.

FIG. 2D

is an example user interface for a client system agent, including incentive advertising, according to the present invention.

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.

FIG. 3B

is a block diagram for servers systems, customer systems, client systems and outsourced host systems, according to the present invention.

FIG. 3C

is a block diagram for a server system processor, according to the present invention.

FIG. 3D

is an alternative block diagram for a server system processor, according to the present invention.

FIG. 4

is a functional block diagram for an example sweepstakes incentive operation according to the present invention.

FIG. 5A

is a block diagram for a distributed processing system for a network site indexing application, according to the present invention.

FIG. 5B

is a functional block diagram for an indexing operation according to the present invention.

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.

FIG. 6B

is a functional block diagram for client capabilities balancing of workloads according to the present invention.

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.

FIG. 7B

is a functional block diagram for site-testing, according to the present invention.

FIG. 8

is a block diagram of a distributed processing system for a data backup application, according to the present invention.

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.

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.

FIG. 11A

is a more detailed flow diagram for machine generated sweepstakes entries according to the present invention.

FIG. 11B

is an alternative detailed flow diagram for machine generated sweepstakes entries according to the present invention.

FIG. 12A

is a block diagram of a distributed processing system that allows customers to select client system attributes, according to the present invention.

FIG. 12B

is a block flow diagram for client system attribute selection, according to the present invention.

FIG. 13A

is a block diagram of a distributed processing system that provides data conversion services, according to the present invention.

FIG. 13B

is a block flow diagram for data conversion services within a distributed processing system, according to the present invention.

FIG. 14A

is a block diagram of a distributed processing system that provides data transmission caching, according to the present invention.

FIG. 14B

is a block diagram of a distributed processing system that provides data sharing and file distribution, according to the present invention.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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 â€œaccept clientsâ€ block 402. Following line 418, the server systems 104 identifies the capabilities of the client's computer and processing systems in the â€œdetermine client system capabilitiesâ€ block 404. Control passes along line 420 to the â€œdistribute workloads to client systemsâ€ block 406, where the server systems 104 allocates workloads to each client system 108, 1110 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 â€œreceive workload resultsâ€ block 408.

At this point, control passes along line 424 to the â€œdetermine sweepstakes entriesâ€ 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.

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.

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.

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.

Referring back to

FIG. 4

, control passes along line 426 to the â€œprocess entriesâ€ block 412. In this block 412, the sweepstakes entries are processed and stored as desired. Following line 428, â€œend of entry periodâ€ 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 â€œdetermine winnersâ€ block 416. The server system 104 then identifies from among the entries, who the winning client system or systems will be.

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.

FIGS. 1

, 2Aâ€“C, 3Aâ€“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

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.

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

des