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Green intelligence for cloud data centers

Authors: C. Karthik; Mayank Sharma; Kirti Maurya; K. Chandrasekaran 0001;

Green intelligence for cloud data centers

Abstract

In this paper the problem of energy consumption by large data centers has been tackled. Power consumption is major problem from both economic and environmental point of view. One of the main components of data centers is virtualization. We have addressed the problem of Virtual Machine (VM) consolidation in the data center servers using the technique of Bin Completion. Bin Completion is basically an artificial intelligence based algorithm used for bin packing problem. We have scaled up and modified the algorithm to fit our problem statement of VM consolidation and analysed the results obtained against Best Fit algorithm. After that we did an extensive study of the application of machine learning algorithms for the purpose of CPU utilisation prediction and analysed its effects on the overall energy consumption of a data center as well as the SLA violations.

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    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.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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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