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Scheduling of tasks in multiprocessor system using hybrid genetic algorithms
Varghese, B. Hossain, M. Alamgir Dahal, Keshav P.
Varghese, B.
Hossain, M. Alamgir
Dahal, Keshav P.
Publication Date
2007
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© 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
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Accepted for publication
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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.
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.
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Type
Conference paper