Research Article
Hybrid Best-Fit Heuristic for Energy Efficient Virtual Machine Placement in Cloud Data Centers
@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
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.
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.
