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Reseach Article

An ACO Algorithm for Scheduling Data Intensive Application with Various QOS Requirements

by S.Aranganathan, K.M.Mehata
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 27 - Number 10
Year of Publication: 2011
Authors: S.Aranganathan, K.M.Mehata
10.5120/3340-4598

S.Aranganathan, K.M.Mehata . An ACO Algorithm for Scheduling Data Intensive Application with Various QOS Requirements. International Journal of Computer Applications. 27, 10 ( August 2011), 1-5. DOI=10.5120/3340-4598

@article{ 10.5120/3340-4598,
author = { S.Aranganathan, K.M.Mehata },
title = { An ACO Algorithm for Scheduling Data Intensive Application with Various QOS Requirements },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 27 },
number = { 10 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume27/number10/3340-4598/ },
doi = { 10.5120/3340-4598 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:13:22.884252+05:30
%A S.Aranganathan
%A K.M.Mehata
%T An ACO Algorithm for Scheduling Data Intensive Application with Various QOS Requirements
%J International Journal of Computer Applications
%@ 0975-8887
%V 27
%N 10
%P 1-5
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Grid computing is rapidly growing in the distributed heterogeneous environment for utilizing and sharing large scale resources to solve complex scientific problems. The main goal of grid computing is to aggregate the power of widely distributed resources and provide non trivial QOS services to the users. To achieve this goal, an efficient grid scheduling algorithm is required. The problem of scheduling on data intensive application in terms of QOS requirements is challenging and it significantly influences the performance of grids. The existing algorithms for scheduling the data intensive application can only tackle the problems with either system centric or application centric. This paper aims to propose a new algorithm based on ant colony optimization to schedule the data intensive application which combines both application centric and system centric benefits. We formulate the problem and simulation results demonstrate the effectiveness of proposed scheduling algorithm.

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Index Terms

Computer Science
Information Sciences

Keywords

Data intensive scheduling ant algorithm Pheromone intensity