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Energy-efficient virtual machine placement in distributed cloud using NSGA-III algorithm

delete2023-08-26
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OA
AI
A
Arunkumar Gopu
K
Kalaipriyan Thirugnanasambandam
R
R. Rajakumar
A
Ahmed Saeed AlGhamdi
S
Sultan S. Alshamrani
K
K. Maharajan
M
Mamoon Rashid *
DOI:10.1186/s13677-023-00501-ydelete
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Abstract

Abstract

En 中文
Cloud computing is the most widely adapted computing model to process scientific workloads in remote servers accessed through the internet. In the IaaS cloud, the virtual machine (VM) is the execution unit that processes the user workloads. Virtualization enables the execution of multiple virtual machines (VMs) on a single physical machine (PM). Virtual machine placement (VMP) strategically assigns VMs to suitable physical devices within a data center. From the cloud provider's perspective, the virtual machine must be placed optimally to reduce resource wastage to aid economic revenue and develop green data centres. Cloud providers need an efficient methodology to minimize resource wastage, power consumption, and network transmission delay. This paper uses NSGA-III, a multi-objective evolutionary algorithm, to simultaneously reduce the mentioned objectives to obtain a non-dominated solution. The performance metrics (Overall Nondominated Vector Generation and Spacing) of the proposed NSGA-III algorithm is compared with other multi-objective algorithms, namely VEGA, MOGA, SPEA, and NSGA-II. It is observed that the proposed algorithm performs 7% better that the existing algorithm in terms of ONVG and 12% better results in terms of spacing. ANOVA and DMRT statistical tests are used to cross-validate the results.
Keywords:
Cloud computing
Distributed system
Energy efficient
Virtualization
NSGA-III algorithm

Journal

J
Journal of Cloud Computing-Advances Systems and Applications
IF:
4.3
Papers:
760
Citations:
2.2K

Organization

V
vit chennai
Scholars:
1.4K
Papers: 1.3K
Citations: 1
K
kalasalingam academy of research & education
Scholars:
1.4K
Papers: 1.2K
Citations: 3
T
Taif University
Scholars:
5.9K
Papers: 7.0K
Citations: 7.5K
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