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Grid computing methodologies facilitate resource sharing and coordination of problem solving in distributed systems. In the Grid environment, shared resources and users typically span different organizations. Grid resources are distributed in different peers. Optimally assigning jobs to resources is one of the key issues in grid computing. This work introduces a Three Dimensional Matchmaking Model (TDMM) for resource allocation on computational grids. Making scheduler intelligent and measuring user satisfaction level gives accurate prediction of resource allocation. The dynamic dimensional based resource allocation is much more efficient in enhancing the overall performance of services.
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