| dc.contributor.author | Jangiti, Saikishor | |
| dc.date.accessioned | 2023-01-23T07:11:08Z | |
| dc.date.available | 2023-01-23T07:11:08Z | |
| dc.date.issued | 2020 | |
| dc.identifier.uri | https://eudl.eu/doi/10.4108/eai.13-7-2018.162689 | |
| dc.identifier.uri | http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8654 | |
| dc.description.abstract | Cloud 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.iso | en | en_US |
| dc.publisher | EUDL | en_US |
| dc.subject | Computer Science | en_US |
| dc.subject | VM placement | en_US |
| dc.subject | Best Fit Decreasing | en_US |
| dc.subject | Hybrid Heuristics | en_US |
| dc.title | Hybrid Best-Fit Heuristic for Energy Efficient Virtual Machine Placement in Cloud Data Centers | en_US |
| dc.type | Article | en_US |
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