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Reseach Article

Comparison of Efficient Job Scheduling Mechanisms Used in Grid Computing: A Review

by Bharti Arora, Sami Anand
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 11
Year of Publication: 2013
Authors: Bharti Arora, Sami Anand
10.5120/12009-7377

Bharti Arora, Sami Anand . Comparison of Efficient Job Scheduling Mechanisms Used in Grid Computing: A Review. International Journal of Computer Applications. 70, 11 ( May 2013), 39-42. DOI=10.5120/12009-7377

@article{ 10.5120/12009-7377,
author = { Bharti Arora, Sami Anand },
title = { Comparison of Efficient Job Scheduling Mechanisms Used in Grid Computing: A Review },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 11 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 39-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number11/12009-7377/ },
doi = { 10.5120/12009-7377 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:32:37.343981+05:30
%A Bharti Arora
%A Sami Anand
%T Comparison of Efficient Job Scheduling Mechanisms Used in Grid Computing: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 11
%P 39-42
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Availability of fast and reliable internet, high speed networks and powerful computers led to the emergence of a new paradigm known as Grid Computing. Grid computing is a form of distributed computing which enables the users to share the heterogeneousresources which are geographically dispersed to solve a complex problem. The heterogeneous nature and tremendous amount of resources makes Grid scheduling a challenging task. Heuristic scheduling is widely used in grid environment due to its advantage over time and cost. We have performed comparative study on Simulated Annealing algorithms (SA), Taboo search algorithms (TS) are categorized under Local search based . Ant Colony scheduling algorithms (ACS), Genetic algorithms (GA),Particle Swarm Optimization Algorithm (POS) are categorized under Population Based. Motivation of this memorandum is to encourage the amateur researcher in the field of grid computing, so they understand easily the concept of scheduling and can contribute in the development more scheduling algorithm. This study provides a comparative analysis on various scheduling algorithm potentials.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Grid computing job scheduling resource scheduling Algorithm performance