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Energy Efficient VM Selection Using CSOA‐VM Model in Cloud Data Centers

Mandeep Singh Devgan, Tajinder Kumar, Purushottam Sharma, Cheng Cheng Orcid Logo, Shashi Bhushan, Vishal Garg

CAAI Transactions on Intelligence Technology, Volume: 10, Issue: 4, Pages: 1217 - 1234

Swansea University Author: Cheng Cheng Orcid Logo

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    © 2025 The Author(s). CAAI Transactions on Intelligence Technology published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology and Chongqing University of Technology. This is an open access article under the terms of the Creative Commons Attribution License (CC BY).

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DOI (Published version): 10.1049/cit2.70018

Abstract

The cloud data centres evolved with an issue of energy management due to the constant increase in size, complexity and enormous consumption of energy. Energy management is a challenging issue that is critical in cloud data centres and an important concern of research for many researchers. In this pa...

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Published in: CAAI Transactions on Intelligence Technology
ISSN: 2468-6557 2468-2322
Published: Wiley 2025
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa69324
Abstract: The cloud data centres evolved with an issue of energy management due to the constant increase in size, complexity and enormous consumption of energy. Energy management is a challenging issue that is critical in cloud data centres and an important concern of research for many researchers. In this paper, we proposed a cuckoo search (CS)-based optimisation technique for the virtual machine (VM) selection and a novel placement algorithm considering the different constraints. The energy consumption model and the simulation model have been implemented for the efficient selection of VM. The proposed model CSOA-VM not only lessens the violations at the service level agreement (SLA) level but also minimises the VM migrations. The proposed model also saves energy and the performance analysis shows that energy consumption obtained is 1.35 kWh, SLA violation is 9.2 and VM migration is about 268. Thus, there is an improvement in energy consumption of about 1.8% and a 2.1% improvement (reduction) in violations of SLA in comparison to existing techniques.
Keywords: cloud computing, cloud datacenter, energy consumption, VM selection
College: Faculty of Science and Engineering
Funders: Swansea University
Issue: 4
Start Page: 1217
End Page: 1234

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