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An Energy Aware Cost Recovery Approach for Virtual Machine Migration

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Economics of Grids, Clouds, Systems, and Services (GECON 2016)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 10382))

Abstract

Datacenters provide an IT backbone for today’s business and economy, and are the principal electricity consumers for Cloud computing. Various studies suggest that approximately 30% of the running servers in US datacenters are idle and the others are under-utilized, making it possible to save energy and money by using Virtual Machine (VM) consolidation to reduce the number of hosts in use. However, consolidation involves migrations that can be expensive in terms of energy consumption, and sometimes it will be more energy efficient not to consolidate. This paper investigates how migration decisions can be made such that the energy costs involved with the migration are recovered, as only when costs of migration have been recovered will energy start to be saved. We demonstrate through a number of experiments, using the Google workload traces for 12,583 hosts and 1,083,309 tasks, how different VM allocation heuristics, combined with different approaches to migration, will impact on energy efficiency. We suggest, using reasonable assumptions for datacenter setup, that a combination of energy-aware fill-up VM allocation and energy-aware migration, and migration only for relatively long running VMs, provides for optimal energy efficiency.

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Acknowledgements

This work is supported by Department of Computer Science, University of Surrey, UK and Abdul Wali Khan University, Mardan, Pakistan.

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Authors and Affiliations

  1. Department of Computer Science, University of Surrey, Guildford, UK

    Muhammad Zakarya & Lee Gillam

  2. Abdul Wali Khan University, Mardan, Pakistan

    Muhammad Zakarya

Authors
  1. Muhammad Zakarya
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  2. Lee Gillam
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Correspondence to Muhammad Zakarya .

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Editors and Affiliations

  1. Department of Computer Science, University of Zaragoza, Zaragoza, Spain

    José Ángel Bañares

  2. Harokopio University, Tavros, Greece

    Konstantinos Tserpes

  3. Seoul National University, Seoul, Korea (Republic of)

    Jörn Altmann

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Zakarya, M., Gillam, L. (2017). An Energy Aware Cost Recovery Approach for Virtual Machine Migration. In: Bañares, J., Tserpes, K., Altmann, J. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2016. Lecture Notes in Computer Science(), vol 10382. Springer, Cham. https://doi.org/10.1007/978-3-319-61920-0_13

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  • DOI: https://doi.org/10.1007/978-3-319-61920-0_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61919-4

  • Online ISBN: 978-3-319-61920-0

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