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Erschienen in: Cluster Computing 3/2020

28.11.2019

Energy-efficiency virtual machine placement based on binary gravitational search algorithm

verfasst von: Foudil Abdessamia, Wei-Zhe Zhang, Yu-Chu Tian

Erschienen in: Cluster Computing | Ausgabe 3/2020

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Abstract

Cloud computing is a remarkable growing paradigm for hosting and offering services through the Internet. It attracted the most notorious business companies and resulted to an exponential increase of its users from simple end users to companies that deploy more and more of their system over the cloud. The amount of resources to provide the demand became tremendous. therefore, a great need energy supply. The world as we know is highly concerned about the environment and the energy-efficiency in all aspect of life and the domain of IT is one them. To deal with energy wastage in data centers, researches use Virtual machine placement as a main key to assure cloud consolidation and reduce power wastage. Several approaches were proposed for Virtual machine placement. This paper proposes a solution based on Binary gravitational search algorithm (BGSA) for the virtual machine placement in the heterogeneous data center. In this work, we compared the BGSA method to fit with virtual machines in data centers with particle swarm optimization, First-fit, Best-fit, and worst-fit. results showed significant difference of energy save comparing to other strategies. The results obtained gave the advantage to our approach and its better response with the increase of number of virtual machines.

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Metadaten
Titel
Energy-efficiency virtual machine placement based on binary gravitational search algorithm
verfasst von
Foudil Abdessamia
Wei-Zhe Zhang
Yu-Chu Tian
Publikationsdatum
28.11.2019
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe 3/2020
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-019-03021-0

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