Energy-efficient fuzzy-based approach for dynamic virtual machine consolidation

In cloud environments, the overload leads to performance degradation and Service Level Agreement (SLA) violation while underload results in inefficient utilisation of resources and needless energy consumption. Dynamic Virtual Machine (VM) consolidation is considered as an effective solution to deal with both overload and underload problems. However, dynamic VM consolidation is not a trivial solution as it can also lead to violation of negotiated SLA due to runtime overheads in VM migration. Further, dynamic VM consolidation approaches need to answer many questions such as (i) when to migrate a VM? (ii) which VM is to be migrated? and (iii) where to migrate the selected VM? In this work, efforts are made to develop a comprehensive approach to achieve better solution to above discussed problems. In the proposed approach, future forecasting methods for host overload detection are explored; a fuzzy logic based VM selection approach that enhances the performance of VM selection strategy is developed; and a VM placement algorithm based on destination CPU utilisation is also developed. The performance evaluation of the proposed approaches is carried out on CloudSim toolkit using PlanetLab data set. The simulation results have exhibited significant improvement in the number of VM migrations, energy consumption, and SLA violations.