Multi-objective optimization for VM placement in homogeneous and heterogeneous cloud service provider data centers


We address the virtual machine placement problem that arises in Cloud Service Providers data centers. We purpose, a Multi-Objective Integer Linear Programming model which aims at optimizing simultaneously the number of hosted virtual machines, the resource wastage and the number of active physical machines (PM) in order to minimize power consumption. This new combination of objectives enables to maximize the client satisfaction rate with minimizing the data center (DC) operational costs. We modelize this problem with a multi-objective integer linear program and solve it through two different methods. The first method computes a unique solution for a given preference order over the objectives whereas the second computes a set of non-dominated solutions. Both methods are compared through extensive simulation scenarios. We consider two DC architectures: homogeneous DCs (i.e., a DC with PMs having the same amount of resources) and heterogeneous DCs. We study the impact of each DC configuration on the performances of the solutions. We show that the second method leads to solutions with a reduction of up to 30% over the number of used PMs and that the heterogeneous DCs outperforms the homogeneous one across all objectives.

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Correspondence to Rym Regaieg.

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Regaieg, R., Koubàa, M., Ales, Z. et al. Multi-objective optimization for VM placement in homogeneous and heterogeneous cloud service provider data centers. Computing (2021).

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  • Virtual machine placement
  • MILP model
  • Weighted sum method
  • Knee point

Mathematics Subject Classification

  • 90C05