Dynamic resource management in virtualized data centers with bursty traffic

Reducing energy consumption in data centers has been a persistent goal for the last decade. Advances in virtualization and dynamic power management have helped to curb excess utilization by sharing resources and running system components in lower energy states during periods of low traffic. However, switching components among virtual machines and energy states is subject to setup times and increased energy consumption to bring them online, and this combined with the innate burstiness of traffic in data centers are significant deterrents to the successful deployment of power management techniques. In this paper, we develop a queueing model with a controllable service rate that accounts for switching frictions within a setting that has a changing arrival rate. We solve for the optimal control policy using dynamic programming, and find it has intuitive structural properties. We compare its performance against benchmark heuristics, and the relative advantages among them in different scenarios are discussed.