Energy-efficient placement of virtual machines in cloud data centres based on fuzzy decision making. (2018) - Salimian, Leili; Safi-Esfahani, Faramarz
Placement of virtual machines (VMs) on physical nodes as a sub-problem of dynamic VM consolidation has been driven by mainly energy efficiency and performance objectives. However, due to varying workloads in VMs, placement of the VMs can cause a violation in Service Level Agreement (SLA). In this paper, the VM placement is regarded as a bin packing problem, and a fuzzy energy-aware algorithm is proposed to estimate the host resource usage. The estimated resource usage is used to find the most energy-efficient host to reallocate the VMs. The fuzzy algorithm generates rules and membership functions dynamically to adapt to workload changes. The main objective of the proposed algorithm is to optimise the energy-performance trade-off. The effectiveness of the proposed algorithm is evaluated through simulations on the random and real-world PlanetLab workloads. Simulation results demonstrate that the proposed algorithm reduces the energy consumption, while it provides a high level of adherence to the SLAs.