DocumentCode :
123774
Title :
Energy-Efficient Virtual Machines Placement
Author :
De La Vigliotti, Albert P. M. ; Macedo Batista, Daniel
Author_Institution :
Dept. of Comput. Sci., Univ. of Sao Paulo, Sao Paulo, Brazil
fYear :
2014
fDate :
5-9 May 2014
Firstpage :
1
Lastpage :
8
Abstract :
Energy efficiency on computer systems is a topic that is gaining a lot of interest. Even more in the cloud computing era, where data centres consumption corresponds to near 1.5% of total world wide power consumption. In this paper we present two novel approaches for virtual machines (VMs) placement consolidation. The two approaches aim to maximize the placed VMs on a host and therefore minimize the number of hosts used on a cloud computing environment. The first proposed approach is based on the Knapsack problem and the second one is based on an Evolutionary Computation heuristic. Both strategies have shown consumed energy reduction starting from 40.33% and up to 92.21% compared to a strategy that does not consider energy efficiency.
Keywords :
cloud computing; computer centres; evolutionary computation; knapsack problems; power aware computing; virtual machines; VM; cloud computing environment; computer systems; consumed energy reduction; data centers consumption; energy-efficient virtual machines placement; evolutionary computation heuristic; knapsack problem; Cloud computing; Computational modeling; Containers; Libraries; Resource management; Virtual machining; Virtualization; cloud computing; green cloud; power efficiency; virtual machines consolidation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Networks and Distributed Systems (SBRC), 2014 Brazilian Symposium on
Conference_Location :
Florianopolis
Type :
conf
DOI :
10.1109/SBRC.2014.1
Filename :
6927113
Link To Document :
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