Optimal sleep-wake scheduling for energy harvesting smart mobile devices

In this paper, we develop optimal sleep/wake scheduling algorithms for smart mobile devices that are powered by finite capacity batteries and are capable of harvesting energy from the environment. Using a novel combination of the two-timescale Lyapunov optimization approach and the weight perturbation technique, we design the Optimal Sleep/wake scheduling Algorithm (OSA), which does not require any statistical knowledge of the harvestable energy process. We prove that OSA is able to achieve any system performance that is within O(ε) of the optimal, and explicitly compute the required battery size, which is O(1=ε).