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dc.contributor.authorKarthik, C.
dc.contributor.authorSharma, M.
dc.contributor.authorMaurya, K.
dc.contributor.authorChandrasekaran, K.
dc.date.accessioned2020-03-30T10:18:08Z-
dc.date.available2020-03-30T10:18:08Z-
dc.date.issued2016
dc.identifier.citation2016 3rd International Conference on Recent Advances in Information Technology, RAIT 2016, 2016, Vol., , pp.591-597en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/8156-
dc.description.abstractIn 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. � 2016 IEEE.en_US
dc.titleGreen intelligence for cloud data centersen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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