Optimality analysis of energy-performance trade-off for server farm management

A central question in designing server farms today is how to efficiently provision the number of servers to extract the best performance under unpredictable demand patterns while not wasting energy While one would like to turn servers off when they become idle to save energy the large setup cost (both in terms of setup time and energy penalty) needed to switch the server back on can adversely affect performance The problem is made more complex by the fact that today s servers provide multiple sleep or standby states which trade off the setup cost with the power consumed while the server is sleeping With so many controls finding the optimal server farm management policy is an almost intractable problem - How many servers should be on at any given time how many should be off and how many should be in some sleep state? In this paper we employ the popular metric of Energy-Response time Product (ERP) to capture the energy-performance trade-off and present the first theoretical results on the optimality of server farm management policies For a stationary demand pattern we prove that there exists a very small natural class of policies that always contains the optimal policy for a single server and conjecture it to contain a near-optimal policy for multi-server systems For time-varying demand patterns we propose a simple traffic-oblivious policy and provide analytical and empirical evidence for its near-optimality (C) 2010 Elsevier B V All rights reserved