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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 8, 2023.
Abstract: Cloud data centers use virtualization technology to manage computing resources. Using a group of connected Virtual Machines (VMs), corresponding users can compute data efficiently and effectively. It improves the utilization of resources, thereby reducing hardware requirements. Repossession of affected services requires VM-based infrastructure overhaul schemes. Clarifications concerning dedicated routing are also desirable to improve the reliability of Domain Controller (DC) services. The migration of a VM experiencing a node failure challenges maintaining reliability. The selection of VMs is influential in limiting the number of VM migrations. Choosing one or more potential VMs for migration reduces the servers' workload. This paper presents an energy-aware VM migration method for cloud computing based on the Black Widow Optimization (BWO) algorithm. The proposed algorithm was implemented and measured using JAVA. Afterward, we compared our results against existing methodologies regarding resource availability, energy consumption, load, and migration cost.
Chuang Zhou, “Black Widow Optimization Algorithm for Virtual Machines Migration in the Cloud Environments” International Journal of Advanced Computer Science and Applications(IJACSA), 14(8), 2023. http://dx.doi.org/10.14569/IJACSA.2023.01408100
@article{Zhou2023,
title = {Black Widow Optimization Algorithm for Virtual Machines Migration in the Cloud Environments},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.01408100},
url = {http://dx.doi.org/10.14569/IJACSA.2023.01408100},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {8},
author = {Chuang Zhou}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.