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...

全面介绍

书目详细资料
发表在:2024 6th IEEE Symposium on Computers and Informatics, ISCI 2024
主要作者: 2-s2.0-85204989411
格式: Conference paper
语言:English
出版: Institute of Electrical and Electronics Engineers Inc. 2024
在线阅读:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204989411&doi=10.1109%2fISCI62787.2024.10668096&partnerID=40&md5=e2992e44c32d1bb487e26ca7bff80b7b
实物特征
总结: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.
ISSN:
DOI:10.1109/ISCI62787.2024.10668096