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Workload Consolidation using VM Selection and Placement Techniques in Cloud Computing

by Monika Patel, Hiren Patel, Nimisha Patel
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 137 - Number 4
Year of Publication: 2016
Authors: Monika Patel, Hiren Patel, Nimisha Patel
10.5120/ijca2016908676

Monika Patel, Hiren Patel, Nimisha Patel . Workload Consolidation using VM Selection and Placement Techniques in Cloud Computing. International Journal of Computer Applications. 137, 4 ( March 2016), 8-11. DOI=10.5120/ijca2016908676

@article{ 10.5120/ijca2016908676,
author = { Monika Patel, Hiren Patel, Nimisha Patel },
title = { Workload Consolidation using VM Selection and Placement Techniques in Cloud Computing },
journal = { International Journal of Computer Applications },
issue_date = { March 2016 },
volume = { 137 },
number = { 4 },
month = { March },
year = { 2016 },
issn = { 0975-8887 },
pages = { 8-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume137/number4/24261-2016908676/ },
doi = { 10.5120/ijca2016908676 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:37:25.595210+05:30
%A Monika Patel
%A Hiren Patel
%A Nimisha Patel
%T Workload Consolidation using VM Selection and Placement Techniques in Cloud Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 137
%N 4
%P 8-11
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud computing provides a consumer pay-per-use computing model over the Internet using numerous data centers across the globe. Power consumption by the huge data centers in Cloud environment has attracted the attention of research community. Efficient usage of energy in Cloud can be addressed in many facets. Virtual Machine (VM) consolidation is one of the techniques to save or reduce energy in virtualized data centers. VM Migration in Cloud also provides us an opportunity for reducing energy consumption. In this research, we intend to study various VM placements & selection policies and VM migration algorithms for underloaded and overloaded hosts to reduce energy consumption and SLA violation. We propose a novel method using combination of two methods, Least Increase Power (LIP) consumption with Host Sort and Minimum Correlation Coefficient (MCC) for consolidation of VM placement, placing a migratable VM on a host based on utilization thresholds. The results show performance of each combination of algorithms varies with the changing value of the parameters brings better in terms of energy consumption, VM migration time and SLA violation. The reader may plunge the appropriate method for energy consumption.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Energy consumption Virtual Machine consolidation Virtualization VM migration SLA violation Virtual machine placement

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