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Cluster Computing

, Volume 22, Supplement 4, pp 8319–8334 | Cite as

An improved Lévy based whale optimization algorithm for bandwidth-efficient virtual machine placement in cloud computing environment

  • Mohamed Abdel-Basset
  • Laila Abdle-Fatah
  • Arun Kumar SangaiahEmail author
Article

Abstract

The consolidation of virtual machine (VM) is the strategy of efficient and intelligent use of cloud datacenters resources. One of the important subproblems of VM consolidation is VM placement problem. The main objective of VM placement problem is to minimize the number of running physical machines or hosts in cloud datacenters. This paper focuses on solving VM placement problem with respect to the available bandwidth which is formulated as variable sized bin packing problem. Moreover, a new bandwidth allocation policy is developed and hybridized with an improved variant of whale optimization algorithm (WOA) called improved Lévy based whale optimization algorithm. Cloudsim toolkit is used in order to test the validity of the proposed algorithm on 25 different data sets that generated randomly and compared with many optimization algorithms including: WOA, first fit, best fit, particle swarm optimization, genetic algorithm, and intelligent tuned harmony search. The obtained results are analyzed by Friedman test which indicates the prosperity of the proposed algorithm for minimizing the number of running physical machine.

Keywords

Cloud computing Virtual machine placement Variable sized bin packing problem Bandwidth allocation policy Lévy flight Whale optimization algorithm Metaheuristic 

Supplementary material

10586_2018_1769_MOESM1_ESM.doc (88 kb)
Supplementary material 1 (doc 88 KB)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Operations Research, Faculty of Computers and InformaticsZagazig UniversitySharqiyahEgypt
  2. 2.School of Computing Science and EngineeringVellore Institute of TechnologyVelloreIndia

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