An adaptive fuzzy threshold-based approach for energy and performance efficient consolidation of virtual machines

摘要

Dynamic consolidation of virtual machines (VMs) is an effective technique, which can lead to improvement of energy efficiency and resource utilization in cloud data centers. However, due to varying workloads in applications, consolidating the virtual machines can cause a violation in Service Level Agreement. The main goal of the dynamic VM consolidation is to optimize the energy-performance trade-off. Detecting when a host is being overloaded or underloaded are two substantial sub-problems of dynamic VM consolidation, which directly affects the utilization of resources, Quality of Service, and energy efficiency as well. In this paper, an adaptive fuzzy threshold-based algorithm has been proposed to detect overloaded and under-loaded hosts. The proposed algorithm generates rules dynamically and updates membership functions to adapt to changes in workload. It is validated with real-world PlanetLab workload. Simulation results demonstrate that the proposed algorithm significantly outperforms the other competitive algorithms.