ew 19(24): e2

Research Article

Bulk-bin-packing based migration management of reserved virtual machine requests for green cloud computing

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  • @ARTICLE{10.4108/eai.11-6-2019.159605,
    author={Saikishor  Jangiti and Subramaniyaswamy V and Shankar Sriram V. S.},
    title={Bulk-bin-packing based migration management of reserved virtual machine requests for green cloud computing},
    journal={EAI Endorsed Transactions on Energy Web},
    volume={6},
    number={24},
    publisher={EAI},
    journal_a={EW},
    year={2019},
    month={7},
    keywords={VM Consolidation, reserved instances, standard instances, bulk-bin-packing, cloud computing, energy-efficiency},
    doi={10.4108/eai.11-6-2019.159605}
}
  • Saikishor Jangiti
    Subramaniyaswamy V
    Shankar Sriram V. S.
    Year: 2019
    Bulk-bin-packing based migration management of reserved virtual machine requests for green cloud computing
    EW
    EAI
    DOI: 10.4108/eai.11-6-2019.159605
Saikishor Jangiti1, Subramaniyaswamy V2, Shankar Sriram V. S.1,*
  • 1: Center for Information Super Highway (CISH), SASTRA Deemed University, Thanjavur, Tamilnadu, India.
  • 2: School of Computing, SASTRA Deemed University, Thanjavur, Tamilnadu, India.
*Contact email: sriram@it.sastra.edu

Abstract

The dynamic consolidation of Virtual Machines (VMs) into a minimum number of Physical Machines (PMs) is a key energy-efficient practice in a cloud data centre, to reduce the running PMs and save electricity costs. We proposed a migration based VM consolidation approach for reserved requests. Real Dataset EC2 was used in the simulation experiments. The proposed BBPMM has demonstrated the elastic capability of adjusting the running PMs and it reduced 38% of running PMs in a reservation transition period.

Keywords
VM Consolidation, reserved instances, standard instances, bulk-bin-packing, cloud computing, energy-efficiency
Received
2019-05-07
Accepted
2019-05-29
Published
2019-07-23
Publisher
EAI
http://dx.doi.org/10.4108/eai.11-6-2019.159605

Copyright © 2019 Saikishor Jangiti et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.