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International Conference on Advanced Information Networking and Applications

AINA 2022: Advanced Information Networking and Applications pp 24–36Cite as

An Energy Consumption Model of Servers to Make Virtual Machines Migrate

Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 449)

Abstract

It is critical to reduce the electric energy consumption of information systems to realize green societies. In this paper, we discuss the migration approach to reducing the energy consumption of servers by taking advantage of live migration technologies of virtual machines. We propose a VM (Virtual machine Migration) algorithm to make virtual machines migrate from a host server to a guest server so that the total energy consumption of the servers can be reduced. In the evaluation, we show the total energy consumption of servers in a cluster can be reduced in the VM algorithm compared with other algorithms.

Keywords

  • Server selection algorithm
  • Migration of virtual machines
  • Green computing systems
  • Estimation algorithm

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  • DOI: 10.1007/978-3-030-99584-3_3
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Author information

Authors and Affiliations

  1. RCCMS, Hosei University, Tokyo, Japan

    Dilawaer Duolikun & Makoto Takizawa

  2. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

  3. Department of Information and Communications Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

Authors
  1. Dilawaer Duolikun
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  2. Tomoya Enokido
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  3. Leonard Barolli
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  4. Makoto Takizawa
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Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Prof. Dr. Leonard Barolli

  2. University of Technology Sydney, Sydney, NSW, Australia

    Dr. Farookh Hussain

  3. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Prof. Dr. Tomoya Enokido

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Duolikun, D., Enokido, T., Barolli, L., Takizawa, M. (2022). An Energy Consumption Model of Servers to Make Virtual Machines Migrate. In: Barolli, L., Hussain, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2022. Lecture Notes in Networks and Systems, vol 449. Springer, Cham. https://doi.org/10.1007/978-3-030-99584-3_3

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