Optimal Power-Aware Design in a Cluster System: Markov Decision Process Approach

Dynamic power management (DPM) plays a significant role to save the power consumption effectively in both design and operational phases of computer-based systems. Especially, it is well known that the state-dependent control policy by monitoring the energy state in each component or the whole system is efficient for power saving in server systems whose system state such as the number of transaction requests can be completely observed. In this paper we consider an optimal power-aware design in a cluster system and formulate the DPM problem by means of a Markov decision process. We derive the dynamic programming equation for the optimal control policy which maximizes the expected reward per unit electrical power, called the power effectiveness, and give a policy iteration algorithm to determine the optimal control policy sequentially. In a numerical example, we consider a cluster system with two service nodes and describe the arrival stream of the transaction request process by a Markov modulated Poisson process. It is shown that the optimal control policy maximizing the power effectiveness is given in the form of decision table.