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Efficient Resources Allocation for Different Jobs in Cloud

by K. Dinesh, G. Poornima, K. Kiruthika
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 56 - Number 10
Year of Publication: 2012
Authors: K. Dinesh, G. Poornima, K. Kiruthika
10.5120/8928-3005

K. Dinesh, G. Poornima, K. Kiruthika . Efficient Resources Allocation for Different Jobs in Cloud. International Journal of Computer Applications. 56, 10 ( October 2012), 30-35. DOI=10.5120/8928-3005

@article{ 10.5120/8928-3005,
author = { K. Dinesh, G. Poornima, K. Kiruthika },
title = { Efficient Resources Allocation for Different Jobs in Cloud },
journal = { International Journal of Computer Applications },
issue_date = { October 2012 },
volume = { 56 },
number = { 10 },
month = { October },
year = { 2012 },
issn = { 0975-8887 },
pages = { 30-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume56/number10/8928-3005/ },
doi = { 10.5120/8928-3005 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:58:29.621946+05:30
%A K. Dinesh
%A G. Poornima
%A K. Kiruthika
%T Efficient Resources Allocation for Different Jobs in Cloud
%J International Journal of Computer Applications
%@ 0975-8887
%V 56
%N 10
%P 30-35
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud Computing is an emerging technique in recent years that provides computing as a services. In order to maximize resources utilization, many scheduling algorithms were analyzed and implemented. Job scheduling using Berger model is one of the algorithm for scheduling jobs. The combination of Berger model and Neural Network would overcome the disadvantage of Berger Model i. e. , incompletion of task when tasks-resources match is not achieved. In this work, the submitted jobs are classified based on different parameters like bandwidth, memory, Completion time and Resources Utilization. The classified user tasks are passed to the neural network. Neural network consists of input layer, hidden layer and output layer. With the help of hidden layer, the jobs are matched with the resources by adjusting weight. The performance of the system has been improved by means of efficient use of bandwidth, reducing a completion time which in turn improves resources utilization. CloudSim, a simulation tool has been used to simulate and the results shows reduced completion time and increased performance of the system.

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Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Job Scheduling Neural Network Berger model CloudSim.

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