MVMM: Data Center Scheduler Algorithm for Virtual Machine Migration

  • Nawel KortasEmail author
  • Habib Youssef
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 926)


Migration algorithms and conception of data centers have significant impact on cost and service qualities. Researchers are looking to find effective solutions for Virtual Machine (VM) migration in data centers to reduce power consumption under the given quality of service constraints. This paper presents a model for the consistency of VM migration in a data center by Dynamic Bayesian Networks (DBN). The novelty of our work is to construct a DBN according to the probabilistic dependencies between the parameters in order to make decisions about the corresponding placement of VM in the distributed data centers. In addition, to evaluate the proposed model, we add a new scheduler algorithm inspiring from the DBN model into GreenCloud simulator, called MVMM (Minimization of Virtual Machine Migration), which provides a VM score to make decisions about the matching placement of VMs in order to allow a minimization of future VMs migrations. The results reveal that the use of the proposed approach can reduce energy consumption until 8% compared to other scheduler algorithms.


Virtual machine Data center Cloud computing Dynamic Bayesian Networks SLA VM migration algorithm 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Prince Research Laboratory, ISITCom of Hammam SousseUniversity of SousseSousseTunisia

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