International Journal of Computer Networks and Applications (IJCNA)

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International Journal of Computer Networks and Applications (IJCNA)

International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

Optimizing Virtual Machines Placement in a Heterogeneous Cloud Data Center System

Author NameAuthor Details

Aristide Ndayikengurukiye, Abderrahmane Ez-Zahout, Fouzia Omary

Aristide Ndayikengurukiye[1]

Abderrahmane Ez-Zahout[2]

Fouzia Omary[3]

[1]Intelligent Processing and Security of Systems Team, Faculty of Sciences, Mohammed V University, Rabat, Morocco.

[2]Intelligent Processing and Security of Systems Team, Faculty of Sciences, Mohammed V University, Rabat, Morocco.

[3]Intelligent Processing and Security of Systems Team, Faculty of Sciences, Mohammed V University, Rabat, Morocco.

Cite this Article

DOI: 10.22247/ijcna/2024/224431

Pages : 1-12

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Abstract

In a cloud computing environment, good resource management remains a major challenge for its good operation. Implementing virtual machine placement (VMP) on physical machines helps to achieve various objectives, such as resource allocation, load balancing, energy consumption, and quality of service. VMP (virtual machine placement) in the cloud is critical, so it's important to audit its implementation. It must take into account the resources of the physical server, including CPU, RAM, and storage. In this paper, a metaheuristic algorithm based on the Grey Wolf Optimization (GWO) method is used to optimize the placement of virtual machines in a cloud environment, effectively minimizing the number of active virtual machines used to host virtual servers. Experimental results demonstrate the effectiveness of the proposed method, called Grey Wolf Optimization for Virtual Machine Placement (GWOVMP). The method reduces power consumption by 20.99 and resource wastage by 1.80 compared with existing algorithms.

Index Terms

Cloud Computing

GWO Algorithm

Metaheuristics Algorithm

Optimization

Virtual Machine Placement

Data Center

Power Consumption

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