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Open AccessArticle

Virtual Machine Replication on Achieving Energy-Efficiency in a Cloud

Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
Laboratory for Analysis of System Dependability, Kawasaki 210-0832, Japan
Authors to whom correspondence should be addressed.
Academic Editor: Wolfgang Bein
Electronics 2016, 5(3), 37;
Received: 1 June 2016 / Revised: 22 June 2016 / Accepted: 27 June 2016 / Published: 1 July 2016
(This article belongs to the Special Issue Energy Saving in Data Centers)
The rapid growth in cloud service demand has led to the establishment of large-scale virtualized data centers in which virtual machines (VMs) are used to handle user requests for service. A user’s request cannot be completed if the VM fails. Replication mechanisms can be used to mitigate the impact of failures. Further, data centers consume a large amount of energy resulting in high operating costs and contributing to significant greenhouse gas (GHG) emissions. In this paper, we focus on Infrastructure as a Service (IaaS) cloud where user job requests are processed by VMs and analyze the effectiveness of VM replications in terms of job completion time performance as well as energy consumption. Three different schemes: cold, warm, and hot replications are considered. The trade-offs between job completion time and energy consumption in different replication schemes are characterized through comprehensive analytical models which capture VM state transitions and associated power consumption patterns. The effectiveness of replication schemes are demonstrated through experimental results. To verify the validity of the proposed analytical models, we extend the widely used cloud simulator CloudSim and compare the simulation results with analytical solutions. View Full-Text
Keywords: cloud; power; energy; fault tolerance; replication; job completion time; structure-state process cloud; power; energy; fault tolerance; replication; job completion time; structure-state process
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MDPI and ACS Style

Mondal, S.K.; Muppala, J.K.; Machida, F. Virtual Machine Replication on Achieving Energy-Efficiency in a Cloud. Electronics 2016, 5, 37.

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