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Task Scheduling in Parallel Systems using Genetic Algorithm

by Rachhpal Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 108 - Number 16
Year of Publication: 2014
Authors: Rachhpal Singh
10.5120/18999-0470

Rachhpal Singh . Task Scheduling in Parallel Systems using Genetic Algorithm. International Journal of Computer Applications. 108, 16 ( December 2014), 34-40. DOI=10.5120/18999-0470

@article{ 10.5120/18999-0470,
author = { Rachhpal Singh },
title = { Task Scheduling in Parallel Systems using Genetic Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 108 },
number = { 16 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 34-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume108/number16/18999-0470/ },
doi = { 10.5120/18999-0470 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:43:11.400342+05:30
%A Rachhpal Singh
%T Task Scheduling in Parallel Systems using Genetic Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 108
%N 16
%P 34-40
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The common problem of multiprocessor scheduling can be defined as allocating a task graph in a multiprocessor system so that schedule length can be improved. Task scheduling in multiprocessor system is a NP-complete problem. A number of heuristic methods have been cultivated that achieve partial solutions in less than the minimum computing time. Genetic algorithms have obtained much awareness as they are robust and provide a good solution. In this paper, genetic algorithm based on the principles of evolution to obtain an optimal solution for task scheduling is developed. Genetic algorithm is based on three operators: Natural Selection, Crossover and Mutation. The simulation results prove that the method proposed generates better results.

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Index Terms

Computer Science
Information Sciences

Keywords

Parallel computing Heterogeneous system Task scheduling Task duplication Schedule length and Load balance.

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