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- W3152938721 abstract "Cloud computing paradigm provides on demand utilities to the customers and involves high resource requirements. Virtual machine allocation plays a vital role in the optimization of resource usage in a data center. This approach consolidates workload on minimal number of servers to improve their resource utilization and thus contributes to energy efficiency. The literature evidences number of virtual machine allocation strategies that vary considerably in adopted approaches and evaluation environments. This research work aims to analyze performance of commonly used heuristic allocation policies. To ensure logistic comparison, the selection of policies is done that implements bin-packing approach in allocation. These algorithms are intensively compared to different workload data-sets and varying experimental setups. Performance of these algorithms with different threshold and virtual machine selection policies is also evaluated. The results conclude that the policies which consider power and computing capacity of the server perform better in almost all scenarios." @default.
- W3152938721 created "2021-04-26" @default.
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- W3152938721 date "2021-01-01" @default.
- W3152938721 modified "2023-09-24" @default.
- W3152938721 title "Performance Evaluation of VM Allocation Strategies on Heterogeneous Environments in Cloud Data Center" @default.
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- W3152938721 doi "https://doi.org/10.1007/978-981-33-4299-6_43" @default.
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