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- W2103179184 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 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." @default.
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- W2103179184 date "2009-01-01" @default.
- W2103179184 modified "2023-10-14" @default.
- W2103179184 title "Scheduling Meta-Tasks in Distributed Heterogeneous Computing Systems: A Meta-Heuristic Particle Swarm Optimization Approach" @default.
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- W2103179184 doi "https://doi.org/10.1109/his.2009.293" @default.
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