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2009

Scheduling Meta-Tasks in Distributed Heterogeneous Computing Systems: A Meta-Heuristic Particle Swarm Optimization Approach

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Scheduling Meta-Tasks in Distributed Heterogeneous Computing Systems: A Meta-Heuristic Particle Swarm Optimization Approach
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.
Hesam Izakian, Ajith Abraham, Václav Sn&aac
Added 18 Feb 2011
Updated 18 Feb 2011
Type Journal
Year 2009
Where HIS
Authors Hesam Izakian, Ajith Abraham, Václav Snásel
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