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    Scheduling of tasks in multiprocessor system using hybrid genetic algorithms

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    Publication date
    2007
    Author
    Varghese, B.
    Hossain, M. Alamgir
    Dahal, Keshav P.
    Keyword
    Optimal scheduling
    Hard real-time tasks
    Multiprocessor system
    Heuristics
    Genetic algorithms
    Rights
    © 2007 Springer Verlag. Reproduced in accordance with the publisher's self-archiving policy. Original publication is available at http://www.springerlink.com
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    This paper presents an investigation into the optimal scheduling of realtime tasks of a multiprocessor system using hybrid genetic algorithms (GAs). A comparative study of heuristic approaches such as `Earliest Deadline First (EDF)¿ and `Shortest Computation Time First (SCTF)¿ and genetic algorithm is explored and demonstrated. The results of the simulation study using MATLAB is presented and discussed. Finally, conclusions are drawn from the results obtained that genetic algorithm can be used for scheduling of real-time tasks to meet deadlines, in turn to obtain high processor utilization.
    URI
    http://hdl.handle.net/10454/2552
    Version
    Accepted Manuscript
    Citation
    Varghes, B., Hossain, M. A. and Dahal, K. P. (2007) Scheduling of tasks in multiprocessor system using hybrid genetic algorithms. In: Kacprzyk, J.(ed.) Advances in soft computing: Updating the state of the art. (12th Online World Conference on Soft Computing in Industrial Applications. (WSC12) October 16th- 26th, 2007). Berlin: Springer. pp. 65-74.
    Link to publisher’s version
    http://www.springerlink.com
    Type
    Conference paper
    Collections
    Engineering and Informatics Publications

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