[1] | Radu Prodan, Ennio Torre, Juan J. Durillo, Gagangeet Singh Aujla, Neeraj Kummar, Hamid Mohammadi Fard, Shajulin Benedikt, Dynamic Multi-objective Virtual Machine Placement in Cloud Data Centers, In 2019 45th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), IEEE, pp. 92-99, 2019.
[bib][url] [doi] [abstract]
Abstract: Minimizing the resource wastage reduces the energy cost of operating a data center, but may also lead to a considerably high resource overcommitment affecting the Quality of Service (QoS) of the running applications. Determining the effective tradeoff between resource wastage and overcommitment is a challenging task in virtualized Cloud data centers and depends on how Virtual Machines (VMs) are allocated to physical resources. In this paper, we propose a multi-objective framework for dynamic placement of VMs exploiting live-migration mechanisms which simultaneously optimize the resource wastage, overcommitment ratio and migration cost. The optimization algorithm is based on a novel evolutionary meta-heuristic using an island population model underneath. We implemented and validated our method based on an enhanced version of a well-known simulator. The results demonstrate that our approach outperforms other related approaches by reducing up to 57% migrations energy consumption while achieving different energy and QoS goals.
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