DESC:AUGMENTING COMPUTATIONAL GRID WITH CAPABILITY OF DATA PARALLEL EXECUTION ON NETWORK EDGE ,CLAIMS:1. A method for augmenting grid capacity, the method comprising:
receiving, by a middleware system (112), idle resource information for a future time interval from each of a plurality of edge devices (108);
determining, by the middleware system (112), a cumulative capacity estimate for each time slot in the future time interval based on the idle resource information;
receiving, by the middleware system (112), job information for a job to be handled by the edge device (108), wherein the job information is received from a grid server (104) in response to providing the cumulative capacity estimate; and
partitioning, by the middleware system (112), the job based on the job information and the idle resource information to generate task allocation information for allocating tasks to the edge devices (108) to augment grid capacity.
2. The method as claimed in claim 1, further comprising receiving, by the middleware system (112), results generated by the edge devices (108) on execution of the allocated tasks and combining the results to obtain a combined result.
3. The method as claimed in claim 2, further comprising sending, by the middleware system (112), the combined result to the grid server as the overall result of the job provided by the grid server (104).
4. The method as claimed in claim 1, wherein the determining the cumulative capacity estimate is based on benchmarking the idle resource information against an average grid resource.
5. The method as claimed in claim 1, wherein the idle resource information is based on user experience feedback and a categorization of applications at respective edge device (108).

6. A middleware system (112) for augmenting grid capacity, the middleware system (112) comprising:
a pooling and abstraction unit (114) to:
receive idle resource information for a future interval from each of a plurality of edge devices (108); and
determine a cumulative capacity estimate for each time slot in the future time interval based on the idle resource information;
a job reception unit (210) to receive job information for a job to be handled by the edge devices (108), wherein the job information is received from a grid server (104) in response to providing the cumulative capacity estimate; and
a scheduling and capacity based partitioning unit (214) to partition the job based on the job information and the idle resource information to generate task allocation information for allocating tasks to the edge devices (108) to augment the grid capacity.
7. The middleware system (112) as claimed in claim 6, further comprising a result combiner unit (230) to combine results generated by the edge devices (108) on execution of the allocated tasks to obtain a combined result.
8. The middleware system (112) as claimed in claim 7, further comprising a middleware process agent (208) to receive the job information from the grid server (104) and provide the combined result to the grid server (104) as an overall result of the job provided by the grid server (104).
9. The middleware system (112) as claimed in claim 6, wherein the pooling and abstraction unit (114) determines the cumulative capacity estimate based on benchmarking the idle resource information against an average grid resource.

10. A network comprising a grid infrastructure (100) and edge devices (108), wherein the grid infrastructure (100) comprises:
a grid server (104) to perform and coordinate operations in the grid infrastructure (100); and
a middleware system (112) to coordinate task allocation and result collation between the edge devices (108) and the grid server (104), the middleware system (112) comprising a pooling and abstraction unit (114) to determine a cumulative capacity estimate for each time slot in a future time interval based on idle resource information received from each of the edge devices (108);
wherein each of the edge devices (108) comprises a user experience (UE) based capacity manager (110) to determine idle resource information for the future time interval based at least on UE feedback and to provide the idle resource information to the middleware system (112);
wherein the grid server (104) provides the job to the middleware system (112), based on the cumulative capacity estimate, for determining task allocation for each of the edge devices (108); and
wherein the middleware system (112) partitions the job into tasks, determines the task allocation for each of the edge devices (108) based on the idle resource information, and combines the results of task execution received from each of the edge devices (108) to provide a combined result to the grid server (104).