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Framework for Task Scheduling in Heterogeneous Distributed Computing Using Genetic Algorithms

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Abstract

An algorithm has been developed to dynamically schedule heterogeneous tasks on heterogeneous processors in a distributed system. The scheduler operates in an environment with dynamically changing resources and adapts to variable system resources. It operates in a batch fashion and utilises a genetic algorithm to minimise the total execution time. We have compared our scheduler to six other schedulers, three batch-mode and three immediate-mode schedulers. Experiments show that the algorithm outperforms each of the others and can achieve near optimal efficiency, with up to 100,000 tasks being scheduled

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Authors and Affiliations

  1. Department of Computer Science, National University of Ireland, Maynooth, County Kildare, Ireland

    Andrew J. Page & Thomas J. Naughton

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  1. Andrew J. Page
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  2. Thomas J. Naughton
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Correspondence to Andrew J. Page.

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Page, A.J., Naughton, T.J. Framework for Task Scheduling in Heterogeneous Distributed Computing Using Genetic Algorithms. Artif Intell Rev 24, 415–429 (2005). https://doi.org/10.1007/s10462-005-9002-x

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  • DOI: https://doi.org/10.1007/s10462-005-9002-x

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