Grid scheduling: Comparative study of MACO & TABU search
Keywords:
Grid Computing, job scheduling, ACO, MACO, tabu searchAbstract
Grid computing is progressively considered as a Next-generation computational platform that supports wide-area parallel and distributed computing. Scheduling jobs to resources in grid computing is difficult due to the distributed and heterogeneous nature of the resources. In Grid computing finding optimal schedules for such an environment is (in general) an NP-hard problem, and so heuristic technique must be used. The aim of grid task scheduling is to achieve high system throughput and to distribute various computing resources to applications. Many different algorithms have been proposed to solve this problem. Some of these algorithms are based on heuristic techniques that provide an Optimal or near optimal solution for large grids.In this paper shows the grid scheduling algorithms and comparison between them.
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