Battery-aware power management based on Markovian decision processes

This paper addresses the problem of maximizing the capacity utilization of the battery power source in a portable electronic system under latency and loss rate constraints. First, a detailed stochastic model of a power-managed battery-powered electronic system is presented. The model, which is based on the theories of continuous-time Markovian decision processes (CTMDP) and stochastic networks, captures two important characteristics of today's rechargeable battery cells; i.e., the current rate-capacity characteristic and the relaxation induced capacity recovery. Next, the battery-aware dynamic power management (DPM) problem is formulated as a policy optimization problem and is solved by using a linear programming approach. Experimental results show that the proposed method outperforms existing methods by more than 20% in terms of battery service lifetime.