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Energy-Efficient Virtual Machines Placement

Authors: Albert P. M. De La Fuente Vigliotti; Daniel Macêdo Batista;

Energy-Efficient Virtual Machines Placement

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.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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