ew 20(26): e4

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.