An Overview of the State-of-the-art Virtual Machine Placement Algorithms for Green Cloud Data Centres

Anindya  Bose; Sanjay  Nag

doi:10.46977/apjmt.2022v03i01.001

Authors

Anindya Bose Dept. of Computational Science, Brainware University, West Bengal 700125, Kolkata, India
Sanjay Nag Department of Computational Science, Brainware University, West Bengal 700125, Kolkata, India

DOI:

https://doi.org/10.46977/apjmt.2022v03i01.001%20

Keywords:

Cloud Data Centres, Virtual Machine, Physical Machine, Server Consolidation

Abstract

Increased energy consumption in Cloud Data Centres (CDCs) increases the carbon footprint. Efficiency of the data centres thus needs to be improved through server consolidation using effective virtual machine (VM) placement and migration techniques and minimizing the number of active physical machines (PMs). One of the problems is how to operationally allocate the VMs to PMs. These allocations have both operational costs and energy consumption issues. To achieve the aim of ‘Green Computing’ a number of state-of-the-art machine learning algorithms have been proposed for the VM placement. The authors of this paper have provided a detailed discussion and comparison of some of the current research works on energy efficiency. and cons of each of these techniques have been discussed. Some future research prospects in this field have also been mentioned at the end.

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