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...
| الحاوية / القاعدة: | 2024 6th IEEE Symposium on Computers and Informatics, ISCI 2024 |
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| المؤلف الرئيسي: | |
| التنسيق: | Conference paper |
| اللغة: | English |
| منشور في: |
Institute of Electrical and Electronics Engineers Inc.
2024
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| الوصول للمادة أونلاين: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204989411&doi=10.1109%2fISCI62787.2024.10668096&partnerID=40&md5=e2992e44c32d1bb487e26ca7bff80b7b |
| الملخص: | 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. |
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| تدمد: | |
| DOI: | 10.1109/ISCI62787.2024.10668096 |