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    Framework for task scheduling in heterogeneous distributed computing using genetic algorithms


    Page, Andrew J. and Naughton, Thomas J. (2005) Framework for task scheduling in heterogeneous distributed computing using genetic algorithms. Artificial Intelligence Review, 24 (3-4). pp. 415-429.

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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.

    Item Type: Article
    Keywords: distributed computing; task scheduling; genetic algorithms;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 570
    Depositing User: Thomas Naughton
    Date Deposited: 21 Jun 2007
    Journal or Publication Title: Artificial Intelligence Review
    Publisher: Springer
    Refereed: Yes
    URI:

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