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Energy-Efficient Virtual Machine Scheduling across Cloudlets in Wireless Metropolitan Area Networks

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Abstract

Nowadays, with the development of wireless communication, people are relying on mobile devices heavily due to various application deployment and plentiful service experience of customers in wireless metropolitan area network (WMAN). The computing resources of the mobile devices are limited as they are restricted with physical size, battery capacity, etc. In order to release the resource limitation, cloudlet, an effective paradigm, is introduced to host the computing tasks offloaded from the mobile devices. Compared with the cloud computing, the cloudlets are deployed closer to provide customers with fewer task offloading delay. Currently, the offloaded task scale is increasing, which generates large quantities of energy exposure for task implementation among cloudlets. Taking advantage of live virtual machine (VM) migration technology, the energy consumption of cloudlets could be definitely reduced. But such migration across cloudlets also decreases the implementation performance of the tasks. Therefore, it is still a challenge to jointly optimize the execution performance and the energy consumption for cloudlet management in WMAN. In this paper, a novel virtual machine (VM) scheduling method is proposed to balance the implantation time and the energy consumption to cope with the above challenge. Specifically, a collection of available migration polices are obtained through heuristically searching of destination cloudlets for the running computing tasks. Then, simple additive weighting (SAW) and multiple criteria decision making (MCDM) techniques are leveraged to select the optimal VM scheduling strategy across cloudlets in WMAN. Finally, experimental results and evaluations validate our proposed method is both effective and feasible.

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Acknowledgments

This research is supported by the National Natural Science Foundation of China under grant no.61702277 and no.61872219. This work is also supported by The Startup Foundation for Introducing Talent of NUIST, the open project from the Skate Key Laboratory for Novel Software Technology, Nanjing University, under grant no. KFKT2017B04, the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) fund, and Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET).

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Authors and Affiliations

  1. School of Computer and Software, Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing, China

    Xiaolong Xu

  2. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China

    Xihua Liu & Yuhao Chen

  3. School of Information Science and Engineering, Qufu Normal University, Shandong, China

    Lianyong Qi

  4. School of Information and Software Engineering, University of Electronic Science and Techonology of China, Chengdu, China

    Zihao Ding

  5. Shanghai Shang Da Hai Run Information System Co., Ltd, Shanghai, China

    Jiangang Shi

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  1. Xiaolong Xu
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  2. Xihua Liu
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  4. Yuhao Chen
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Correspondence to Jiangang Shi.

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Xu, X., Liu, X., Qi, L. et al. Energy-Efficient Virtual Machine Scheduling across Cloudlets in Wireless Metropolitan Area Networks. Mobile Netw Appl 25, 442–456 (2020). https://doi.org/10.1007/s11036-019-01242-6

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