Energy-Efficient Virtual Machine Placement in Data Centers by Ant Colony Optimization Algorithm (ACO)

In the era of burgeoning cloud computing adoption worldwide, energy efficiency emerges as a critical concern due to the escalating power consumption necessary for ensuring server stability. This paper presents a study utilizing Ant Colony Optimization algorithm (ACO) as an alternative approach to ac...

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Published in:2024 6th IEEE Symposium on Computers and Informatics, ISCI 2024
Main Author: Suliman S.I.; Mutalib A.R.I.A.; Yusof Y.W.M.; Rahman F.Y.A.; Shahbudin S.
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204989411&doi=10.1109%2fISCI62787.2024.10668096&partnerID=40&md5=e2992e44c32d1bb487e26ca7bff80b7b
id 2-s2.0-85204989411
spelling 2-s2.0-85204989411
Suliman S.I.; Mutalib A.R.I.A.; Yusof Y.W.M.; Rahman F.Y.A.; Shahbudin S.
Energy-Efficient Virtual Machine Placement in Data Centers by Ant Colony Optimization Algorithm (ACO)
2024
2024 6th IEEE Symposium on Computers and Informatics, ISCI 2024


10.1109/ISCI62787.2024.10668096
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204989411&doi=10.1109%2fISCI62787.2024.10668096&partnerID=40&md5=e2992e44c32d1bb487e26ca7bff80b7b
In the era of burgeoning cloud computing adoption worldwide, energy efficiency emerges as a critical concern due to the escalating power consumption necessary for ensuring server stability. This paper presents a study utilizing Ant Colony Optimization algorithm (ACO) as an alternative approach to achieving energy-efficient virtual machine placement in data centers. It is aimed at mitigating the growing energy demands within these infrastructures. The study focuses on optimizing power consumption to assess the efficacy of the ant colony optimization technique in minimizing energy usage within data centers. The ACO technique is selected to strategically place virtual machines, aiming to minimize power consumption in data centers. Experimental results demonstrate that the proposed method effectively reduces the power consumption of physical machines while fulfilling all system operating constraints. © 2024 IEEE.
Institute of Electrical and Electronics Engineers Inc.

English
Conference paper

author Suliman S.I.; Mutalib A.R.I.A.; Yusof Y.W.M.; Rahman F.Y.A.; Shahbudin S.
spellingShingle Suliman S.I.; Mutalib A.R.I.A.; Yusof Y.W.M.; Rahman F.Y.A.; Shahbudin S.
Energy-Efficient Virtual Machine Placement in Data Centers by Ant Colony Optimization Algorithm (ACO)
author_facet Suliman S.I.; Mutalib A.R.I.A.; Yusof Y.W.M.; Rahman F.Y.A.; Shahbudin S.
author_sort Suliman S.I.; Mutalib A.R.I.A.; Yusof Y.W.M.; Rahman F.Y.A.; Shahbudin S.
title Energy-Efficient Virtual Machine Placement in Data Centers by Ant Colony Optimization Algorithm (ACO)
title_short Energy-Efficient Virtual Machine Placement in Data Centers by Ant Colony Optimization Algorithm (ACO)
title_full Energy-Efficient Virtual Machine Placement in Data Centers by Ant Colony Optimization Algorithm (ACO)
title_fullStr Energy-Efficient Virtual Machine Placement in Data Centers by Ant Colony Optimization Algorithm (ACO)
title_full_unstemmed Energy-Efficient Virtual Machine Placement in Data Centers by Ant Colony Optimization Algorithm (ACO)
title_sort Energy-Efficient Virtual Machine Placement in Data Centers by Ant Colony Optimization Algorithm (ACO)
publishDate 2024
container_title 2024 6th IEEE Symposium on Computers and Informatics, ISCI 2024
container_volume
container_issue
doi_str_mv 10.1109/ISCI62787.2024.10668096
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204989411&doi=10.1109%2fISCI62787.2024.10668096&partnerID=40&md5=e2992e44c32d1bb487e26ca7bff80b7b
description In the era of burgeoning cloud computing adoption worldwide, energy efficiency emerges as a critical concern due to the escalating power consumption necessary for ensuring server stability. This paper presents a study utilizing Ant Colony Optimization algorithm (ACO) as an alternative approach to achieving energy-efficient virtual machine placement in data centers. It is aimed at mitigating the growing energy demands within these infrastructures. The study focuses on optimizing power consumption to assess the efficacy of the ant colony optimization technique in minimizing energy usage within data centers. The ACO technique is selected to strategically place virtual machines, aiming to minimize power consumption in data centers. Experimental results demonstrate that the proposed method effectively reduces the power consumption of physical machines while fulfilling all system operating constraints. © 2024 IEEE.
publisher Institute of Electrical and Electronics Engineers Inc.
issn
language English
format Conference paper
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record_format scopus
collection Scopus
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