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Energy Efficient Virtual Machine Optimization

by Vikram Yadav, Pooja Malik, Ajay Singh Chauhan, G. Sahoo
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 106 - Number 7
Year of Publication: 2014
Authors: Vikram Yadav, Pooja Malik, Ajay Singh Chauhan, G. Sahoo
10.5120/18533-9741

Vikram Yadav, Pooja Malik, Ajay Singh Chauhan, G. Sahoo . Energy Efficient Virtual Machine Optimization. International Journal of Computer Applications. 106, 7 ( November 2014), 23-28. DOI=10.5120/18533-9741

@article{ 10.5120/18533-9741,
author = { Vikram Yadav, Pooja Malik, Ajay Singh Chauhan, G. Sahoo },
title = { Energy Efficient Virtual Machine Optimization },
journal = { International Journal of Computer Applications },
issue_date = { November 2014 },
volume = { 106 },
number = { 7 },
month = { November },
year = { 2014 },
issn = { 0975-8887 },
pages = { 23-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume106/number7/18533-9741/ },
doi = { 10.5120/18533-9741 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:38:46.760156+05:30
%A Vikram Yadav
%A Pooja Malik
%A Ajay Singh Chauhan
%A G. Sahoo
%T Energy Efficient Virtual Machine Optimization
%J International Journal of Computer Applications
%@ 0975-8887
%V 106
%N 7
%P 23-28
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The optimization of energy consumption in the cloud computing environment is the question how to use various energy conservation strategies to efficiently allocate resources. The need of different resources in cloud environment is unpredictable. It is observed that load management in cloud is utmost needed in order to provide QOS. The jobs at over-loaded physical machine are shifted to under-loaded physical machine and turning the idle machine off in order to provide green cloud. For energy optimization, DVFS and Power-Nap are good strategies. As much of this energy is wasted in idle systems: in typical deployments, server utilization is below 30%, but idle servers still consume 60% of their peak power draw. In this paper, we have proposed an hybrid approach for energy optimization using Ant Colony optimization, Bee Colony optimization, PowerNap, DVFS and RAILS having the constraint QOS.

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Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Hadoop BigData DVFS Power-Nap Ant colony algorithm bee colony algorithm etc.

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