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 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.

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Publication Details

Published
2024-08-10
DOI
https://doi.org/10.1109/isci62787.2024.10668096
Citations
2
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
1.56

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article

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

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article

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

Farah Rahman, Shahrani Shahbudin, Saiful Izwan Suliman, Yuslinda Wati Mohamad Yusof, Abdul Rahman Ikmal Abdul Mutalib
article en
2 citations

Abstract

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.

Universiti Teknologi MARA (MY)
Universiti Teknologi MARA
Affordable and clean energy
Openalex Percentile: Top 13%
Cloud Computing and Resource Management
1.56
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