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DOI: 10.14569/IJACSA.2023.0140576
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Krill Herd Algorithm for Live Virtual Machines Migration in Cloud Environments

Author 1: Hui Cao
Author 2: Zhuo Hou

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 5, 2023.

  • Abstract and Keywords
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Abstract: Green cloud computing is a modern approach that provides pay-per-use information and communication technologies with a minimal carbon footprint. Cloud computing enables users to access computing resources without the need for local servers or personal devices to operate applications. It allows businesses and developers to access infrastructure and hardware resources conveniently. Consequently, this results in a growing demand for data centers. It becomes crucial in maintaining economic and environmental sustainability as data centers use disproportionate energy. This points to sustainability and energy consumption as being important topics for research in cloud computing. This paper introduces a two-tiered VM placement algorithm. A queuing model is proposed at the first level to handle many VM requests. Models such as cloud simulation are easily implemented and validated using this model. It also provides an alternate method for allocating tasks to servers. Next, a multi-objective VM placement algorithm is proposed based on the Krill Herd (KH) algorithm. Basically, it maintains a balance between energy consumption and resource utilization.

Keywords: Cloud computing; migration; virtualization; energy consumption

Hui Cao and Zhuo Hou, “Krill Herd Algorithm for Live Virtual Machines Migration in Cloud Environments” International Journal of Advanced Computer Science and Applications(IJACSA), 14(5), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140576

@article{Cao2023,
title = {Krill Herd Algorithm for Live Virtual Machines Migration in Cloud Environments},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140576},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140576},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {5},
author = {Hui Cao and Zhuo Hou}
}



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.

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