Metaheuristic Based Scheduling Meta-Tasks in Distributed Heterogeneous Computing SystemsReport as inadecuate




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1

Islamic Azad University, Ramsar Branch, Ramsar, Iran

2

Machine Intelligence Research Labs MIR Labs, Auburn, Washington 98071-2259, USA

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Norwegian Center of Excellence, Center of Excellence for Quantifiable Quality of Service, Norwegian University of Science and Technology, O.S. Bragstads plass 2E, N-7491 Trondheim, Norway

4

Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava, Czech Republic





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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. View Full-Text

Keywords: distributed heterogeneous computing systems; particle swarm optimization; scheduling distributed heterogeneous computing systems; particle swarm optimization; scheduling





Author: Hesam Izakian 1, Ajith Abraham 2,3,* and Václav Snášel 2,4

Source: http://mdpi.com/



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