Performance impact of the MVMM algorithm for virtual machine migration in data centres

Virtual machine (VM) migration mechanisms and the design of data centres for the cloud have a significant impact on energy cost and SLA constraints. The recent work focuses on how to use VM migration to achieve stable physical machine utilisation with the objective of reducing energy consumption, understated SLA constraints. This paper presents and evaluates a new scheduling algorithm called MVMM (Minimisation of Virtual Machine Migration) for VM. It makes use of a DBN (Dynamic Bayesian Network) to decide where and when a particular VM migrates. Indeed, the DBN takes as input the data centre parameters then computes a score for each VM candidate for migration in order to reduce the energy consumption by decreasing the number of future migrations according to the probabilistic dependencies between the data centre parameters. The performance results show that the use of the MVMM algorithm can reduce energy consumption by up to 35%.