A clustered virtual machine allocation strategy based on a sleep-mode with wake-up threshold in a cloud environment

Shunfu Jin (), Xiuchen Qie (), Wenjuan Zhao (), Wuyi Yue () and Yutaka Takahashi ()
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Shunfu Jin: Yanshan University
Xiuchen Qie: Yanshan University
Wenjuan Zhao: Yanshan University
Wuyi Yue: Konan University
Yutaka Takahashi: Kyoto University

Annals of Operations Research, 2020, vol. 293, issue 1, No 10, 193-212

Abstract: Abstract The massive amount of energy consumed by cloud data centers is detrimentally impacting on the environments. As such, to work towards “greener” computing, in this paper, we propose a clustered virtual machine (VM) allocation strategy based on a sleep-mode with a wake-up threshold. The VMs in a cloud data center are clustered into two pools, namely, Pool I and Pool II. The VMs in Pool I remain awake at all times, while the VMs in Pool II go to sleep under a light workload. After a sleep timer expires, the corresponding VM will resume processing tasks only if the number of waiting tasks reaches the wake-up threshold. Otherwise, the sleeping VM will remain asleep as a new sleep timer starts. By establishing a queue with an N-policy and asynchronous vacations of partial servers, we capture the stochastic behavior of tasks with the proposed strategy, and derive the performance measures in terms of the average latency of tasks and the energy saving rate of the system. Furthermore, we provide numerical results to demonstrate the impact of the system parameters on the system performance. Finally, we construct a system cost function to trade off different performance measures, and develop an intelligent searching algorithm to jointly optimize the number of the VMs in Pool II, the wake-up threshold and the sleeping parameter.

Keywords: Cloud data center; Clustered VM allocation; Wake-up threshold; Sleep-mode; Average latency; Energy saving rate (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10479-019-03339-3

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