Metaheuristic based scheduling meta-tasks in distributed heterogeneous computing systems

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Show simple item record Izakian, Hesam Abraham, Ajith Snášel, Václav 2009-09-18T07:16:40Z 2009-09-18T07:16:40Z 2009
dc.identifier.citation Sensors. 2009, vol. 9, issue 7, p. 5339-5350. en
dc.identifier.issn 1424-8220
dc.description.abstract Scheduling is a key problem in distributed heterogeneous computing systems in order to benefit from the large computing capacity of such systems and is an NP-complete problem. In this paper, we present a metaheuristic technique, namely the Particle Swarm Optimization (PSO) algorithm, for this problem. PSO is a population-based search algorithm based on the simulation of the social behavior of bird flocking and fish schooling. Particles fly in problem search space to find optimal or near-optimal solutions. The scheduler aims at minimizing makespan, which is the time when finishes the latest task. Experimental studies show that the proposed method is more efficient and surpasses those of reported PSO and GA approaches for this problem. en
dc.format.extent 130973 bytes cs
dc.format.mimetype application/pdf cs
dc.language.iso en en
dc.publisher Molecular Diversity Preservation International en
dc.relation.ispartofseries Sensors en
dc.relation.uri en
dc.subject distributed heterogeneous computing systems en
dc.subject particle swarm optimization en
dc.subject scheduling en
dc.title Metaheuristic based scheduling meta-tasks in distributed heterogeneous computing systems en
dc.type article en
dc.identifier.location Není ve fondu ÚK en
dc.identifier.doi 10.3390/s90705339
dc.rights.access openAccess
dc.type.version publishedVersion
dc.identifier.wos 000268317000016

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