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dc.contributor.authorVarghese, B.
dc.contributor.authorHossain, M. Alamgir
dc.contributor.authorDahal, Keshav P.
dc.date.accessioned2009-04-07T13:49:21Z
dc.date.available2009-04-07T13:49:21Z
dc.date.issued2007
dc.identifier.citationVarghes, 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.en
dc.identifier.urihttp://hdl.handle.net/10454/2552
dc.description.abstractThis 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.en
dc.language.isoenen
dc.publisherSpringer Verlagen
dc.relation.isreferencedbyhttp://www.springerlink.comen
dc.rights© 2007 Springer Verlag. Reproduced in accordance with the publisher's self-archiving policy. Original publication is available at http://www.springerlink.comen
dc.subjectOptimal schedulingen
dc.subjectHard real-time tasksen
dc.subjectMultiprocessor systemen
dc.subjectHeuristicsen
dc.subjectGenetic algorithmsen
dc.titleScheduling of tasks in multiprocessor system using hybrid genetic algorithmsen
dc.status.refereedYesen
dc.typeConference paperen
dc.type.versionAccepted Manuscripten
refterms.dateFOA2018-07-18T02:19:43Z


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