Abstract: Various embodiments enable network service providers to receive revenue from their user bases by providing network services to various distributed devices in exchange for the distributed devices agreeing to process workloads for customer paid projects. In at least one embodiment, a method of operating a distributed processing system may include identifying a first party with a first user base with several first distributed devices, and identifying a different party with a different user base with several second distributed devices. Processing workloads for a customer paid project using the first and second distributed devices. Then, sharing revenue from the customer project between the first party and the second party based in part on a size of a user base, a user base's processing capability, or a type of project processed by the user base.

Abstract: Software-based network attached storage (NAS) services are hosted on a massively distributed processing system configured by coupling a multiplicity of distributed devices with a network, wherein each of the distributed devices are enabled to process workloads for the distributed processing system by a client agent program. More particularly, the client agent program is configured with a NAS software component to enable selected distributed devices from the multiplicity of distributed devices to appear to client devices coupled to the network as dedicated NAS devices. The NAS software component allocates an available amount of storage resources in the selected distributed devices to provide NAS services to the client devices. Storage priority controls, including user specified constraints, standard bit, block and file priority levels, and direct bit, block or file priority markings may be utilized to facilitate the full use of the available amounts of unused storage in the selected distributed devices.

Abstract: Various embodiments enable a server system to identify a workload capability factor for a distributed device and use the workload capability factor to determine an incentive for the distributed device. In one embodiment, a distributed processing system includes a server configured to be coupled to one or more distributed devices. The server may include a workload database configured to store at least one workload project, a capability database configured to store one or more workload capability factors associated with one or more distributed devices, and a control system configured to use the one or more workload capability factors from the capability database to perform at least one workload project from the workload database. The least one workload capability factor may also be used to determine an incentive for the one or more distributed devices.

Abstract: A method for providing data conversion services 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.

Abstract: A massively distributed processing system and associated methods are described that utilize an advantageous processing architecture for a multitude of widely distributed devices to process distributed workloads for a plurality distributed processing projects. To provide the infrastructure processing power for the distributed processing system, a modular client agent program, including a system component with a core agent module and a separate project component with at least one task module, is configured to operate on the distributed devices and to process a variety of project workloads. For each different distributed project, different project components or task modules may be provided by a server system to the distributed devices to run on the core agent module or system component. In addition, a capabilities database can be used by a server system to schedule workloads based upon the capabilities of the distributed devices.

Abstract: A method and system for migrating data to a build-to-order computing system is provided. The method comprises storing an image at a remote site. The image comprises data stored on a computing system. An order is received to provide a second computing system to a customer. Access to the image is provided to the second computing system such that the second computing system can store the image.

Abstract: An adsorption cooling system and cooling method as disclosed. An energy storage system is arranged to capture and store energy generated by the adsorption cooling system that is determined to be surplus to the energy needed to meet the current demands for cooling by the adsorption cooling system. The energy storage system is arranged to store said energy for subsequent use.

Abstract: A solar thermal panel is disclosed. The solar thermal panel includes a body, the body comprising a plurality of rubber particles bound by a binding agent and defining one or more channels within the body, the or each channel including a fluid inlet and a fluid outlet connectable to a fluid circulation circuit.

Abstract: A sweepstakes incentive model and associated system for a distributed processing system are disclosed that identify the capabilities of distributed devices connected together through a wide variety of communication systems and networks and aggregate these distributed device capabilities to accomplish desired distributed workload objectives.

Abstract: A method and system for migrating data to a build-to-order computing system is provided. The method comprises storing an image at a remote site. The image comprises data stored on a computing system. An order is received to provide a second computing system to a customer. Access to the image is provided to the second computing system such that the second computing system can store the image.

Abstract: A method and system for migrating data to a build-to-order computing system is provided. The method comprises storing an image at a remote site. The image comprises data stored on a computing system. An order is received to provide a second computing system to a customer. Access to the image is provided to the second computing system such that the second computing system can store the image.

Abstract: Various embodiments enable a server system to transmit a test workload to N distributed devices, request that the N distributed devices execute the test workload by requesting a service from a network site, and receive results from the N distributed devices indicating a quality of service received by the N distributed devices. In one embodiment, a computer-implemented method may include: transmitting an incentive to M number of distributed devices to join a distributed processing system, transmitting a test workload to N number of distributed devices, the N distributed devices being a subset of the M distributed devices, sending a request to the N distributed devices to execute the test workload by accessing and requesting at least one service from at least one network site, and receiving results from at least some of the N distributed devices, the results indicating a quality of service provided by the at least one network site to at least some of the N distributed devices.

Abstract: Various embodiments enable a server system to identify a workload capability factor for a distributed device and use the workload capability factor to determine an incentive for the distributed device. In one embodiment, a distributed processing system includes a server configured to be coupled to one or more distributed devices. The server may include a workload database configured to store at least one workload project, a capability database configured to store one or more workload capability factors associated with one or more distributed devices, and a control system configured to use the one or more workload capability factors from the capability database to perform at least one workload project from the workload database. The least one workload capability factor may also be used to determine an incentive for the one or more distributed devices.

Abstract: Various embodiments enable a distributed processing system to index network content. In at least one embodiment, a method of indexing content comprises distributing indexing workloads to various distributed devices over a network, receiving organized indexed workloads from the various distributed devices, and creating a master summary index to receive the organized indexed workloads. In a further embodiment, a content indexing system comprises a server system, a workload database, and a master summary index. The server system can be coupled to a network which is coupled to various distributed devices. The workload database can be coupled to the server system and distributes indexing workloads to the various distributed devices. Finally, the master summary index can receive completed indexing workloads from the various distributed devices.

Abstract: Various embodiments enable network service providers to receive revenue from their user bases by providing network services to various distributed devices in exchange for the distributed devices agreeing to process workloads for customer paid projects. In at least one embodiment, a method of operating a distributed processing system may include identifying a first party with a first user base with several first distributed devices, and identifying a different party with a different user base with several second distributed devices. Processing workloads for a customer paid project using the first and second distributed devices. Then, sharing revenue from the customer project between the first party and the second party based in part on a size of a user base, a user base's processing capability, or a type of project processed by the user base.

Abstract: Various embodiments enable a server system to receive a request to store data, select various distributed devices to store the data, and then send the data to the selected distributed devices. In one embodiment, a method may include: receiving a request to store back-up data on a distributed processing system from a client system, the back-up data having a storage priority, searching a database to identify one or more distributed devices with excess storage capacity, and selecting one or more of the distributed devices to store the back-up data based in part on the back-up data's storage priority. Then, sending the back-up data to one or more selected distributed devices along with retention instructions indicating conditions for retaining and/or deleting the back-up data, and updating an index with addresses for the one or more selected distributed devices that received the back-up data.

Abstract: Various embodiments enable a server system to consider a variety of priorities in determining how to organize, allocate, and manage client workloads in a distributed processing system. In at least one embodiment, a method may include generating a capability vector for one or more distributed devices, the capability vector defining a capability of the one or more distributed devices, determining a client priority for one or more client system, the client priority defining an order that a client system is granted access to submit one or more workloads to a distributed processing system for processing, assigning a workload priority to one or more workloads, the workload priority defining an order in which a workload is submitted to the distributed processing system for processing, and distributing one or more workloads form a client system to one or more distributed devices in response to the capability vector, the client priority, and the workload priority.

Abstract: Various embodiments enable a server system to convert data for client devices by identifying capabilities associated with various distributed devices, and utilizing those capabilities to select distributed devices to convert data.

Abstract: Dynamic coordination and control of network connected devices within a distributed processing platform is disclosed for large-scale network site testing, or for other distributed projects. For network site testing, the distributed processing system utilizes a plurality of client devices which are running a client agent program associated with the distributed computing platform and which are running potentially distinct project modules for the testing of network sites or other projects. The participating client devices can be selected based upon their attributes and can receive test workloads from the distributed processing server systems. In addition, the client devices can send and receive poll communications that may be used during processing of the project to control, manage and coordinate the project activities of the distributed devices.

Abstract: Dynamic coordination and control of network connected devices within a distributed processing platform is disclosed for large-scale network site testing, or for other distributed projects. For network site testing, the distributed processing system utilizes a plurality of client devices which are running a client agent program associated with the distributed computing platform and which are running potentially distinct project modules for the testing of network sites or other projects. The participating client devices can be selected based upon their attributes and can receive test workloads from the distributed processing server systems. In addition, the client devices can send and receive poll communications that may be used during processing of the project to control, manage and coordinate the project activities of the distributed devices.