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An energy-aware heuristic framework for virtual machine consolidation in Cloud computing

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Abstract

Virtual machine (VM) consolidation in Cloud computing provides a great opportunity for energy saving. However, the obligation of providing suitable quality of service to end users leads to the necessity in dealing with energy-performance tradeoff. In this paper, we propose a redesigned energy-aware heuristic framework for VM consolidation to achieve a better energy-performance tradeoff. There are two main contributions in the framework: (1) establish a service level agreement (SLA) violation decision algorithm to decide whether a host is overload with SLA violation; (2) minimum power and maximum utilization policy is then proposed to improve the Minimum Power policy in previous work. Finally, we have evaluated our framework through simulation on large-scale experiments driven by workload traces from more than a thousand VMs, and the results show that our framework outperforms previous work. Specifically, it guarantees 21–34 % decrease in energy consumption, 84–92 % decrease in SLA violation, 87–94 % decrease in energy-performance metric, and 63 % decrease in execution time. And we further discuss why the redesigned framework outperforms the previous design.

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Acknowledgments

Thanks to Anton Beloglazov, who gives us a positive confirmation about the bug [37] in the MinPower policy deployed in CloudSim. As a result, we can correct the policy and finish this paper. This work is partly supported by Natural Science Foundation of China (Grant No. 61070092).

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  1. School of Computer Science and Engineering, South China University of Technology, Guangzhou , 510006, China

    Zhibo Cao & Shoubin Dong

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  1. Zhibo Cao
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  2. Shoubin Dong
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Correspondence to Shoubin Dong.

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Cao, Z., Dong, S. An energy-aware heuristic framework for virtual machine consolidation in Cloud computing. J Supercomput 69, 429–451 (2014). https://doi.org/10.1007/s11227-014-1172-3

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