Metaheuristic Based Scheduling Meta-Tasks in Distributed Heterogeneous Computing Systems

Sensors

Hesam Izakian¹  Ajith Abraham² 

[1] Islamic Azad University, Ramsar Branch, Ramsar, Iran; E-Mail:;Machine Intelligence Research Labs (MIR Labs), Auburn, Washington 98071-2259, USA; http://www.mirlabs.org

关键词: distributed heterogeneous computing systems;    particle swarm optimization;    scheduling;   

DOI  :  10.3390/s90705339

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2009 by the authors; licensee MDPI, Basel, Switzerland