A simulated annealing algorithm for energy efficient virtual machine placement

Wu, Yongqiang, Tang, Maolin, & Fraser, Warren L. (2012) A simulated annealing algorithm for energy efficient virtual machine placement. In IEEE International Conference on Systems, Man, Cybernetics, 14-17 October 2012, COEX, Seoul.

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Improving energy efficiency has become increasingly important in data centers in recent years to reduce the rapidly growing tremendous amounts of electricity consumption. The power dissipation of the physical servers is the root cause of power usage of other systems, such as cooling systems. Many efforts have been made to make data centers more energy efficient. One of them is to minimize the total power consumption of these servers in a data center through virtual machine consolidation, which is implemented by virtual machine placement. The placement problem is often modeled as a bin packing problem. Due to the NP-hard nature of the problem, heuristic solutions such as First Fit and Best Fit algorithms have been often used and have generally good results. However, their performance leaves room for further improvement. In this paper we propose a Simulated Annealing based algorithm, which aims at further improvement from any feasible placement. This is the first published attempt of using SA to solve the VM placement problem to optimize the power consumption. Experimental results show that this SA algorithm can generate better results, saving up to 25 percentage more energy than First Fit Decreasing in an acceptable time frame.

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24 citations in Scopus
12 citations in Web of Science®
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ID Code: 53749
Item Type: Conference Paper
Refereed: Yes
Keywords: Server consolidation, Virtual machine migration, Simulated annealing, Data Center, Cloud computing
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 > QUT Faculties and Divisions > Division of Technology, Information and Library Services
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 IEEE
Copyright Statement: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
Deposited On: 19 Sep 2012 22:49
Last Modified: 10 Jul 2017 22:42

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