A predictive control approach for energy-aware consolidation of virtual machines in cloud computing

The widespread diffusion of Infrastructure-as-a- Service and cloud computing paradigms requires large-scale data centers with thousands of running nodes and high energy demands, thus causing relevant economical and environmental costs. In this perspective, the paper presents an energy-aware consolidation strategy based on predictive control, in which virtual machines are migrated among nodes to reduce the number of active units. To describe a general cloud infras- tructure, a discrete-time dynamic model is presented together with constraints. The migration strategies of virtual machines are obtained by solving finite-horizon optimal control problems involving integer variables. To reduce the computational effort, approximate solutions are searched for via Monte Carlo opti- mization. Besides power savings, the proposed method allows one to reduce violations of the service level agreement and aggressive on/off cycles of nodes. To showcase the effectiveness of the proposed approach, preliminary simulation results are provided.