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An efficient energy-aware method for virtual machine placement in cloud data centers using the cultural algorithm.

Authors :
Mohammadhosseini, Mahdieh
Toroghi Haghighat, Abolfazl
Mahdipour, Ebrahim
Source :
Journal of Supercomputing. Oct2019, Vol. 75 Issue 10, p6904-6933. 30p.
Publication Year :
2019

Abstract

Excessive consumption of energy in cloud data centers whose number is increasing day by day has led to substantial problems. Hence, offering efficient schemes for virtual machine (VM) placement to decrease energy consumption in cloud computing environments has become a significant research field in recent years. In this paper, with the goal of reducing energy consumption in cloud data centers, we present a VM placement method using the cultural algorithm. In the proposed algorithm called balance-based cultural algorithm for virtual machine placement (BCAVMP), a new fitness function is introduced to evaluate VM allocation solutions. In this function, by using the sum of balance vector lengths for each VM placement, balanced utilization of resources is considered. Also, by applying the amount of energy usage in the fitness function, solutions with lower energy consumption are intended. The performance of the proposed method is evaluated using CloudSim simulator. The simulation results indicate that by appropriate VM assignment and resource wastage reduction, energy consumption in cloud data centers can be decreased. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09208542
Volume :
75
Issue :
10
Database :
Academic Search Index
Journal :
Journal of Supercomputing
Publication Type :
Academic Journal
Accession number :
139007295
Full Text :
https://doi.org/10.1007/s11227-019-02909-3