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DC Field | Value | Language |
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dc.contributor.author | Jangiti, Saikishor | - |
dc.date.accessioned | 2023-01-23T06:57:22Z | - |
dc.date.available | 2023-01-23T06:57:22Z | - |
dc.date.issued | 2020-09 | - |
dc.identifier.uri | https://www.sciencedirect.com/science/article/pii/S2210537920301414 | - |
dc.identifier.uri | http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8651 | - |
dc.description.abstract | The rapid rise in the cloud service adoption reflects the growth of Cloud Data Centers' (CDCs) number, size, energy consumption and eco-unfriendly carbon footprints. In CDCs, Virtual Machine Consolidation (VMC) plays a significant role in reducing their energy consumption and thereby reducing the carbon footprints. The state-of-the-art VMC heuristics based on First-Fit Decreasing (FFD) and Dominant Residual Resource (DRR) called DRR-FFD and DRR-BinFill are grouping the VMs based on single VM resource. We attempt to further reduce the energy consumption of CDCs through the proposed EMC2, an energy-efficient VMC framework that employs our multi-resource-fairness based VM selection heuristics, namely VMNeAR-H (Hierarchical), VM NeAR- D (Directed Hierarchical) and VM NeAR-E (Euclidean Distance). A dataset extracted from ENERGY STAR® containing the heterogeneous physical machine resource capacities and their estimated energy consumptions is utilised in the simulation experiments. The proposed EMC2-VMNeAR-D heuristic dominates the existing DRR heuristics in terms of total energy consumed by all the physical machines in the CDC (3.318 % energy savings on average of 40 schedules = 185107 kWh). | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Virtual machine consolidation | en_US |
dc.subject | Cloud computing | en_US |
dc.subject | First-fit decreasing | en_US |
dc.subject | Dominant resource fairness | en_US |
dc.subject | Residual resource ratio | en_US |
dc.title | EMC2: Energy-efficient and multi-resource- fairness virtual machine consolidation in cloud data centres | en_US |
dc.type | Article | en_US |
Appears in Collections: | Department of Computer Science and Information Systems |
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