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  • 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 Particle Swarm Optimization (PSO) approach 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 make-span, 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.
  • 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 Particle Swarm Optimization (PSO) approach 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 make-span, 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)
Title
  • Scheduling Meta-tasks in Distributed Heterogeneous Computing Systems: A Meta-Heuristic Particle Swarm Optimization Approach
  • Scheduling Meta-tasks in Distributed Heterogeneous Computing Systems: A Meta-Heuristic Particle Swarm Optimization Approach (en)
skos:prefLabel
  • Scheduling Meta-tasks in Distributed Heterogeneous Computing Systems: A Meta-Heuristic Particle Swarm Optimization Approach
  • Scheduling Meta-tasks in Distributed Heterogeneous Computing Systems: A Meta-Heuristic Particle Swarm Optimization Approach (en)
skos:notation
  • RIV/61989100:27240/09:86075646!RIV11-GA0-27240___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/09/1494)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
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  • 340337
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27240/09:86075646
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Approach; Optimization; Swarm; Particle; Meta-Heuristic; Systems:; Computing; Heterogeneous; Distributed; Meta-tasks; Scheduling (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [CD44C6FDC602]
http://linked.open...v/mistoKonaniAkce
  • Čína
http://linked.open...i/riv/mistoVydani
  • Los Alamitos, California
http://linked.open...i/riv/nazevZdroje
  • Ninth International Conference on Hybrid Intelligent Systems, 2009. HIS 09
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Abraham Padath, Ajith
  • Snášel, Václav
  • Izakian, Hesam
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000281999600082
http://linked.open.../riv/zahajeniAkce
number of pages
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  • IEEE Computer Society
https://schema.org/isbn
  • 978-0-7695-3745-0
http://localhost/t...ganizacniJednotka
  • 27240
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