Hybrid Best-Fit Heuristic for Energy Efficient Virtual Machine Placement in Cloud Data Centers

Saikishor Jangiti; Vijayakumar V; Subramaniyaswamy V

Research Article

Hybrid Best-Fit Heuristic for Energy Efficient Virtual Machine Placement in Cloud Data Centers

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@ARTICLE{10.4108/eai.13-7-2018.162689,
    author={Saikishor Jangiti and Vijayakumar V and Subramaniyaswamy V},
    title={Hybrid Best-Fit Heuristic for Energy Efficient Virtual Machine Placement in Cloud Data Centers},
    journal={EAI Endorsed Transactions on Energy Web},
    volume={7},
    number={26},
    publisher={EAI},
    journal_a={EW},
    year={2020},
    month={1},
    keywords={VM Placement, Best Fit Decreasing, Hybrid Heuristics},
    doi={10.4108/eai.13-7-2018.162689}
}

Saikishor Jangiti
Vijayakumar V
Subramaniyaswamy V
Year: 2020
Hybrid Best-Fit Heuristic for Energy Efficient Virtual Machine Placement in Cloud Data Centers
EW
EAI
DOI: 10.4108/eai.13-7-2018.162689

Saikishor Jangiti¹, Vijayakumar V², Subramaniyaswamy V¹^,*

1: School of Computing, SASTRA Deemed University, Thanjavur, Tamilnadu, India
2: Lead Data Scientist, Briteyellow Ltd., United Kingdom

*Contact email: vsubramaniyaswamy@gmail.com

Abstract

Cloud Service Providers (CSPs) offers Information Technology services like infrastructure and software to users on a pay as you go basis. Energy consumption is one of the significant challenges faced by Cloud Service Providers (CSP). Virtual Machine (VM) placement is an energy-efficient practice performed in the cloud datacenters. Best-Fit Decreasing (BFD) is a VM placement and is known to give a near-optimal solution in a reasonable time by sorting the VMs in decreasing order. We propose a Hybrid Best-Fit (HBF) Heuristic for VM placements. Experimental results show that HBF is consuming 2.516% and 3.392% less energy compared to Best-Fit and BFD heuristics.

Keywords: VM Placement, Best Fit Decreasing, Hybrid Heuristics

Received: 2019-06-10
Accepted: 2019-11-29
Published: 2020-01-14
Publisher: EAI

: http://dx.doi.org/10.4108/eai.13-7-2018.162689

Copyright © 2020 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.