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Energy-efficient virtual machine placement in data centers by genetic algorithm

Wu, Grant, Tang, Maolin, Tian, Yu-Chu, & Li, Wei (2012) Energy-efficient virtual machine placement in data centers by genetic algorithm. In Lecture Notes on Computer Science, Springer Berlin Heidelberg, Renaissance Doha City Center Hotel, Doha, pp. 315-323.

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Abstract

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.

Impact and interest:

1 citations in Scopus
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ID Code: 53767
Item Type: Conference Paper
Additional Information: Neural Information Processing : 19th International Conference, ICONIP 2012, Doha, Qatar, November 12-15, 2012, Proceedings, Part III
Keywords: Server consolidation, Virtual machine placement, Data center, optimization, Genetic algorithm
DOI: 10.1007/978-3-642-34487-9_39
ISBN: 9783642344862
ISSN: 0302-9743
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > DISTRIBUTED COMPUTING (080500) > Distributed Computing not elsewhere classified (080599)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 Springer
Copyright Statement: The final publication is available at link.springer.com
Deposited On: 21 Sep 2012 09:32
Last Modified: 26 Aug 2013 12:05

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