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A survey : particle swarm optimization-based algorithms for grid computing scheduling systems.

Ambursa, Faruku Umar and Latip, Rohaya (2013) A survey : particle swarm optimization-based algorithms for grid computing scheduling systems. Journal of Computer Science, 9 (12). pp. 1669-1679. ISSN 1549-3636

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Official URL: http://thescipub.com/issue-jcs/9/12

Abstract

Bio-inspired heuristics have been promising in solving complex scheduling optimization problems. Several researches have been conducted to tackle the problems of task scheduling for the heterogeneous and dynamic grid systems using different bio-inspired mechanisms such as Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO). PSO has been proven to have a relatively more promissing performance in dealing with most of the task scheduling challenges. However, to achieve optimum performance, new models and techniques for PSO need to be developed. This study surveys PSObased scheduling algorithms for Grid systems and presents a classification for the various approaches adopted. Meta task-based and workflow-based are the main categories explored. Each scheduling algorithm is described and discussed under the suitable category.

Item Type:Article
Keyword:Particle Swarm Optimization (PSO); Grid computing; Scheduling.
Faculty or Institute:Faculty of Computer Science and Information Technology
Publisher:Science Publications
DOI Number:10.3844/jcssp.2013.1669.1679
Altmetrics:http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3844/jcssp.2013.1669.1679
ID Code:30677
Deposited By: Nida Hidayati Ghazali
Deposited On:03 Jun 2014 15:41
Last Modified:21 Sep 2015 16:39

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