Exploration based Genetic Algorithm for Job Scheduling on Grid Computing

Hanaa Abdelrahman; Mohammed Bakri Bashir; Adil Yousif

doi:10.18495/comengapp.v5i3.181

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Affiliations

Hanaa Abdelrahman
University Science & Technology

Mohammed Bakri Bashir
Shendi University

Adil Yousif
University of Science and Technology, Khartoum

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Exploration based Genetic Algorithm for Job Scheduling on Grid Computing

Hanaa Abdelrahman ,
Mohammed Bakri Bashir ,
Adil Yousif

Vol 5 No 3 (2016)

DOI 10.18495/comengapp.v5i3.181

Submitted: Jan 12, 2001

Published: Oct 12, 2016

Abstract

Grid computing presents a new trend to distribute and Internet computing to coordinate large scale heterogeneous resources providing sharing and problem solving in dynamic, multi- institutional virtual organizations. Scheduling is one of the most important problems in computational grid to increase the performance. Genetic Algorithm is adaptive method that can be used to solve optimization problems, based on the genetic process of biological organisms. The objective of this research is to develop a job scheduling algorithm using genetic algorithm with high exploration processes. To evaluate the proposed scheduling algorithm this study conducted a simulation using GridSim Simulator and a number of different workload. The research found that genetic algorithm get best results when increasing the mutation and these result directly proportional with the increase in the number of job. The paper concluded that, the mutation and exploration process has a good effect on the final execution time when we have large number of jobs. However, in small number of job mutation has no effects.