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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
computer science
Scheduling jobs on computational grids using a fuzzy particle swarm optimization algorithm
Future Generation Computer Systems, Volume 26, No. 8, Year 2010
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Description
Grid computing is a computational framework used to meet growing computational demands. This paper introduces a novel approach based on Particle Swarm Optimization (PSO) for scheduling jobs on computational grids. The representations of the position and velocity of the particles in conventional PSO is extended from the real vectors to fuzzy matrices. The proposed approach is to dynamically generate an optimal schedule so as to complete the tasks within a minimum period of time as well as utilizing the resources in an efficient way. We evaluate the performance of the proposed PSO algorithm with a Genetic Algorithm (GA) and Simulated Annealing (SA) approach. Empirical results illustrate that an important advantage of the PSO algorithm is its speed of convergence and the ability to obtain faster and feasible schedules. © 2010 Elsevier B.V. All rights reserved.
Authors & Co-Authors
Liu, Hongbo
China, Dalian
Dalian Maritime University
China, Dalian
Dalian University of Technology
United States, Auburn
Machine Intelligence Research Labs Mir Labs - Scientific Network for Innovation and Research Excellence
Abraham, Ajith P.
Norway, Trondheim
Norges Teknisk-naturvitenskapelige Universitet
United States, Auburn
Machine Intelligence Research Labs Mir Labs - Scientific Network for Innovation and Research Excellence
Hassanien, Aboul Ella
Egypt, Giza
Faculty of Computers and Artificial Intelligence
United States, Auburn
Machine Intelligence Research Labs Mir Labs - Scientific Network for Innovation and Research Excellence
Statistics
Citations: 222
Authors: 3
Affiliations: 5
Identifiers
Doi:
10.1016/j.future.2009.05.022
ISSN:
0167739X
Research Areas
Genetics And Genomics