Modeling for Dynamic Cloud Scheduling Via Migration of Virtual Machines

Abstract

Cloud brokerage mechanisms are fundamental to reduce the complexity of using multiple cloud infrastructures to achieve optimal placement of virtual machines and avoid the potential vendor lock-in problems. However, current approaches are restricted to static scenarios, where changes in characteristics such as pricing schemes, virtual machine types, and service performance throughout the service life-cycle are ignored. In this paper, we investigate dynamic cloud scheduling use cases where these parameters are continuously changed, and propose a linear integer programming model for dynamic cloud scheduling. Our model can be applied in various scenarios through selections of corresponding objectives and constraints, and offers the flexibility to express different levels of migration overhead when restructuring an existing infrastructure. Finally, our approach is evaluated using commercial clouds parameters in selected simulations for the studied scenarios. Experimental results demonstrate that, with proper parametrizations, our approach is feasible.