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ThinkMind // CLOUD COMPUTING 2017, The Eighth International Conference on Cloud Computing, GRIDs, and Virtualization // View article cloud_computing_2017_6_20_20053


Dynamic Virtual Machine Allocation Based on Adaptive Genetic Algorithm

Authors:
Oleksandr Rolik
Sergii Telenyk
Eduard Zharikov
Volodymyr Samotyy

Keywords: data center; genetic algorithm; virtual machine; resource management

Abstract:
The widespread use of the virtualization paradigm in modern data centers has increased the necessity of improving the management efficiency of virtual machine allocation on physical machines (PM). Modern service providers offer a large number of virtual machine types and settings. The density of virtual machine placement per physical server also complicates the solution of this problem. Under these conditions, for solving such kind of problems, the adaptive genetic algorithm (AGA) is proposed. The proposed algorithm uses parametric and algorithmic adaptation simultaneously by selecting the values for a genetic operator’s parameters and by selecting the probabilities of applying these operators. The AGA is evaluated for the solution of virtual machine allocation problem and demonstrates efficiency compared to the classical and the controlled versions of genetic algorithm.

Pages: 108 to 114

Copyright: Copyright (c) IARIA, 2017

Publication date: February 19, 2017

Published in: conference

ISSN: 2308-4294

ISBN: 978-1-61208-529-6

Location: Athens, Greece

Dates: from February 19, 2017 to February 23, 2017

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