International Journal of Computer Networks and Applications

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Optimizing Virtual Machines Placement in a Heterogeneous Cloud Data Center System


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

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.

Keywords

Cloud Computing, GWO Algorithm, Metaheuristics Algorithm, Optimization, Virtual Machine Placement, Data Center, Power Consumption.
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  • Optimizing Virtual Machines Placement in a Heterogeneous Cloud Data Center System

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Authors

Aristide Ndayikengurukiye
Intelligent Processing and Security of Systems Team, Faculty of Sciences, Mohammed V University, Rabat, Morocco
Abderrahmane Ez-Zahout
Intelligent Processing and Security of Systems Team, Faculty of Sciences, Mohammed V University, Rabat, Morocco
Fouzia Omary
Intelligent Processing and Security of Systems Team, Faculty of Sciences, Mohammed V University, Rabat, Morocco

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.

Keywords


Cloud Computing, GWO Algorithm, Metaheuristics Algorithm, Optimization, Virtual Machine Placement, Data Center, Power Consumption.

References





DOI: https://doi.org/10.22247/ijcna%2F2024%2F224431