Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers

Article

Khoshkholghi, M.A., Derahman, M.N., Abdullah, A., Subramaniam, S. and Othman, M. 2017. Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers. IEEE Access. 5, pp. 10709-10722. https://doi.org/10.1109/ACCESS.2017.2711043
TypeArticle
TitleEnergy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers
AuthorsKhoshkholghi, M.A., Derahman, M.N., Abdullah, A., Subramaniam, S. and Othman, M.
Abstract

Cloud computing has become a significant research area in large-scale computing, because it can share globally distributed resources. Cloud computing has evolved with the development of large-scale data centers, including thousands of servers around the world. However, cloud data centers consume vast amounts of electrical energy, contributing to high-operational costs, and carbon dioxide emissions. Dynamic consolidation of virtual machines (VMs) using live migration and putting idle nodes in sleep mode allows cloud providers to optimize resource utilization and reduce energy consumption. However, aggressive VM consolidation may degrade the performance. Therefore, an energy-performance tradeoff between providing high-quality service to customers and reducing power consumption is desired. In this paper, several novel algorithms are proposed for the dynamic consolidation of VMs in cloud data centers. The aim is to improve the utilization of computing resources and reduce energy consumption under SLA constraints regarding CPU, RAM, and bandwidth. The efficiency of the proposed algorithms is validated by conducting extensive simulations. The results of the evaluation clearly show that the proposed algorithms significantly reduce energy consumption while providing a high level of commitment to the SLA. Based on the proposed algorithms, energy consumption can be reduced by up to 28%, and SLA can be improved up to 87% when compared with the benchmark algorithms.

KeywordsCloud computing; energy efficiency; service level agreement; virtual machine consolidation; data center
Sustainable Development Goals9 Industry, innovation and infrastructure
Middlesex University ThemeCreativity, Culture & Enterprise
PublisherIEEE
JournalIEEE Access
ISSN
Electronic2169-3536
Publication dates
Online01 Jun 2017
Print27 Jun 2017
Publication process dates
Submitted30 Mar 2017
Accepted02 May 2017
Deposited27 Nov 2025
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1109/ACCESS.2017.2711043
Scopus EID2-s2.0-85028766599
Web of Science identifierWOS:000404360000061
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