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General Information
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2009 Vol.1(1): 1-6 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2009.V1.1

A Novel Genetic Algorithm for Static Task Scheduling in Distributed Systems

Amir Masoud Rahmani and Mojtaba Rezvani

Abstract—The static task scheduling problem in distributed systems is very important because of optimal usage of available machines and accepted computation time for scheduling algorithm. Solving this problem using the dynamic programming and the back tracking needs much more time. Therefore, there are more attempts to solve it using the heuristic methods. In this paper, a new genetic algorithm, named TDGASA, is presented which its running time depends on the number of tasks in the scheduling problem. Then, the computation time of TDGASA to find a sub-optimal schedule is improved by Simulated Annealing (SA). The results show that the computation time of the proposed algorithm decreases compared to an existing GA-based algorithm, although, the completion time of the final scheduled task in the system decreases a little.

Index Terms—Genetic algorithm, static task scheduling, distributed systems, simulated annealing, (TDGASA) Task Dependent Genetic Algorithm using Simulated Annealing


Cite: Amir Masoud Rahmani and Mojtaba Rezvani, "A Novel Genetic Algorithm for Static Task Scheduling in Distributed Systems," International Journal of Computer Theory and Engineering vol. 1, no. 1, pp. 1-6, 2009.

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