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Heuristic based task scheduling in multiprocessor systems with genetic algorithm by choosing the eligible processor

In multiprocessor systems, one of the main factors of systems' performance is task scheduling. The well the task be distributed among the processors the well be the performance. Again finding the optimal solution of scheduling the tasks into the processors is NP-complete, that is, it will take a lot of time to find the optimal solution. Many evolutionary algorithms (e.g. Genetic Algorithm, Simulated annealing) are used to reach the near optimal solution in linear time. In this paper we propose a heuristic for genetic algorithm based task scheduling in multiprocessor systems by choosing the eligible processor on educated guess. From comparison it is found that this new heuristic based GA takes less computation time to reach the suboptimal solution.

preprint2012arXivOpen access
Probir RoyMd. Mejbah Ul AlamNishita Das
Distributed, Parallel, and Cluster Computing
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Open access3 authors1 topic
Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
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Probir RoyMd. Mejbah Ul AlamNishita Das

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