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Reseach Article

Intelligent Methods for Resource Allocation in Grid Computing

by Harsh Bansal, Babita Pandey, Kewal Krishan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 47 - Number 6
Year of Publication: 2012
Authors: Harsh Bansal, Babita Pandey, Kewal Krishan
10.5120/7189-9940

Harsh Bansal, Babita Pandey, Kewal Krishan . Intelligent Methods for Resource Allocation in Grid Computing. International Journal of Computer Applications. 47, 6 ( June 2012), 1-5. DOI=10.5120/7189-9940

@article{ 10.5120/7189-9940,
author = { Harsh Bansal, Babita Pandey, Kewal Krishan },
title = { Intelligent Methods for Resource Allocation in Grid Computing },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 47 },
number = { 6 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume47/number6/7189-9940/ },
doi = { 10.5120/7189-9940 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:41:09.281594+05:30
%A Harsh Bansal
%A Babita Pandey
%A Kewal Krishan
%T Intelligent Methods for Resource Allocation in Grid Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 47
%N 6
%P 1-5
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the era of grid computing, resource allocation plays a vital role for assigning the available resources. This paper describes how to reduce the search time for the best available resources and assure instant provisioning of the lately added resources to the grid thereby using clustering and artificial neural networks. The efficacy is achieved through K-Means clustering algorithm which is used to cluster the similar type of resources on the basis of their configuration as high, medium or low thereby decreasing the search time by searching only into the cluster of high availability instead of searching for the best from all of the available resources. Thereafter artificial neural network trained with feed forward propagation is deployed to automatically assign the newly added resources to appropriate cluster. This approach significantly reduces the computational time of resource allocation.

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Index Terms

Computer Science
Information Sciences

Keywords

Grid Computing Resource Allocation K-means Clustering Artificial Neural Networks