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Mining Intelligence and Knowledge Exploration pp 466–474Cite as

Reduce Energy Consumption through Virtual Machine Placement in Cloud Data Centre

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8284))

Abstract

In this paper, energy consumption in the data centre was studied where thousands of servers and other devices runs, energy are utilized to run the server and cooling the environment. Energy consumption can be reduced by switching off the idle server by means of migration of Virtual Machine from under-load Host. Load in cloud computing is maintained by migration of VM from the overloaded Host to a free Host or activate new Host. Based on this study, a reservation technique by using BIN packing was proposed in this paper with an overload detection algorithm. The proposed algorithm RBIN is experimented in 800 servers with 1024 Virtual Machines. From the experimental result, proposed method RBIN reduces energy in higher level.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Karpagam University, Coimbatore, Tamil Nadu, India

    Nongmaithem Ajith Singh & M. Hemalatha

Authors
  1. Nongmaithem Ajith Singh
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  2. M. Hemalatha
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Editor information

Editors and Affiliations

  1. Department of Business Information Systems, FSIC, National University of Ireland, University College Cork, O’Rahilly Buildings, Cork, Ireland

    Rajendra Prasath

  2. Research Centre in Computer Science, V.H.N.Senthikumara Nadar College (Autonomous), 626 001, Virudhunagar, Tamil Nadu, India

    T. Kathirvalavakumar

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© 2013 Springer International Publishing Switzerland

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Singh, N.A., Hemalatha, M. (2013). Reduce Energy Consumption through Virtual Machine Placement in Cloud Data Centre. In: Prasath, R., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. Lecture Notes in Computer Science(), vol 8284. Springer, Cham. https://doi.org/10.1007/978-3-319-03844-5_47

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  • DOI: https://doi.org/10.1007/978-3-319-03844-5_47

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03843-8

  • Online ISBN: 978-3-319-03844-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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