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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/8654
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dc.contributor.authorJangiti, Saikishor-
dc.date.accessioned2023-01-23T07:11:08Z-
dc.date.available2023-01-23T07:11:08Z-
dc.date.issued2020-
dc.identifier.urihttps://eudl.eu/doi/10.4108/eai.13-7-2018.162689-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8654-
dc.description.abstractCloud Service Providers (CSPs) offers Information Technology services like infrastructure and software to users on a pay as you go basis. Energy consumption is one of the significant challenges faced by Cloud Service Providers (CSP). Virtual Machine (VM) placement is an energy-efficient practice performed in the cloud datacenters. Best-Fit Decreasing (BFD) is a VM placement and is known to give a near-optimal solution in a reasonable time by sorting the VMs in decreasing order. We propose a Hybrid Best-Fit (HBF) Heuristic for VM placements. Experimental results show that HBF is consuming 2.516% and 3.392% less energy compared to Best-Fit and BFD heuristics.en_US
dc.language.isoenen_US
dc.publisherEUDLen_US
dc.subjectComputer Scienceen_US
dc.subjectVM placementen_US
dc.subjectBest Fit Decreasingen_US
dc.subjectHybrid Heuristicsen_US
dc.titleHybrid Best-Fit Heuristic for Energy Efficient Virtual Machine Placement in Cloud Data Centersen_US
dc.typeArticleen_US
Appears in Collections:Department of Computer Science and Information Systems

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