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An experimental study on genetic algorithms for resource allocation on grid systems

Author
Xhafa, F.; Barolli, L.; Durresi, A.
Type of activity
Journal article
Journal
Journal of interconnection networks
Date of publication
2007-12
Volume
8
Number
4
First page
427
Last page
443
DOI
https://doi.org/10.1142/S0219265907002119 Open in new window
URL
http://www.worldscientific.com/doi/abs/10.1142/S0219265907002119 Open in new window
Abstract
Computational Grid (CG) is an emerging paradigm in which geographically distributed resources are logically unified as a computational unit. A challenging problem in such systems is the allocation of jobs to resources that minimizes both makespan and flowtime parameters. In this paper, we present an experimental study on Genetic Algorithms (GAs) for scheduling independents jobs to Grid resources based on two replacement strategies: Steady-State GA (SSGA) and Struggle GA (SGA). SSGA distinguishes...
Keywords
Computational grids, ETC simulation model, Genetic algorithm, Job scheduling, Resource allocation
Group of research
ALBCOM - Algorithms, Computational Biology, Complexity and Formal Methods

Participants