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    Dynamic task scheduling using genetic algorithms for heterogeneous distributed computing

    Page, Andrew J. and Naughton, Thomas J. (2005) Dynamic task scheduling using genetic algorithms for heterogeneous distributed computing. In: IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 6. IEEE, 189.1-189.8. ISBN 0769523129

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    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. We have performed simulations with randomly generated task sets, using uniform, normal, and Poisson distributions, whilst varying the communication overheads between the clients and scheduler. We have achieved more efficient results than all other schedulers across a range of different scenarios while scheduling 10,000 tasks on up to 50 heterogeneous processors.

    Item Type: Book Section
    Keywords: Poisson distribution; scheduling; genetic algorithms; batch processing (computers); resource allocation; normal distribution;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 8394
    Identification Number:
    Depositing User: Thomas Naughton
    Date Deposited: 03 Jul 2017 15:46
    Publisher: IEEE
    Refereed: Yes
    Funders: Irish Research Council for Science Engineering and Technology (IRCSET)
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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