Performance Evaluation and Social Optimization of an Energy-Saving Virtual Machine Allocation Scheme Within a Cloud Environment

doi:10.1007/S40305-019-00272-x

Journal of the Operations Research Society of China ›› 2020, Vol. 8 ›› Issue (4): 561-580.doi: 10.1007/S40305-019-00272-x

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Performance Evaluation and Social Optimization of an Energy-Saving Virtual Machine Allocation Scheme Within a Cloud Environment

Xiushuang Wang¹, Jing Zhu¹, Shunfu Jin¹, Wuyi Yue², Yutaka Takahashi³

1 School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, Shandong, China;
2 Department of Intelligence and Informatics, Konan University, Kobe 658-8501, Japan;
3 Graduate School of Informatics, Kyoto University, Kyoto 606-8225, Japan

Received:2018-11-27 Revised:2019-09-08 Online:2020-12-30 Published:2020-12-29
Contact: Shunfu Jin, Xiushuang Wang, Jing Zhu, Wuyi Yue, Yutaka Takahashi E-mail:jsf@ysu.edu.cn;ysuwxs@163.com;zhuj6886@163.com;yue@konan-u.ac.jp;takahashi@i.kyoto-u.ac.jp
Supported by:
This work was supported in part by the National Natural Science Foundation of China (Nos. 61872311, 61973261, 61472342) and Hebei Provincial Natural Science Foundation (No. F2017203141), China, and was supported in part by MEXT and JSPS KAKENHI (Nos. JP17H01825 and JP26280113), Japan.

Abstract

Abstract: Achieving greener cloud computing is non-negligible for the open-source cloud platform. In this paper, we propose a novel virtual machine allocation scheme with a sleep-delay and establish a corresponding mathematical model. Taking into account the number of tasks and the state of the physical machine, we construct a two-dimensional Markov chain and derive the average latency of tasks and the energy-saving degree of the system in the steady state. Moreover, we provide numerical experiments to show the effectiveness of the proposed scheme. Furthermore, we study the Nash equilibrium behavior and the socially optimal behavior of tasks and carry out an improved adaptive genetic algorithm to obtain the socially optimal arrival rate of tasks. Finally, we present a pricing policy for tasks to maximize the social profit when managing the network resource within the cloud environment.

Key words: Cloud computing, Resource allocation scheme, Mathematical analysis, Markov chain, Socially optimization, Genetic algorithm

CLC Number:

Xiushuang Wang, Jing Zhu, Shunfu Jin, Wuyi Yue, Yutaka Takahashi. Performance Evaluation and Social Optimization of an Energy-Saving Virtual Machine Allocation Scheme Within a Cloud Environment[J]. Journal of the Operations Research Society of China, 2020, 8(4): 561-580.

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Performance Evaluation and Social Optimization of an Energy-Saving Virtual Machine Allocation Scheme Within a Cloud Environment

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