Performance Modeling of Transmission Schedulers for Sensor Networks Capable of Energy Harvesting

Energy harvesting is one of the most promising solutions for the enhancing the lifetime of sensor networks by overcoming the limitations of current batter technology. This paper investigates the performance of scheduling strategies for sensor networks with energy harvesting. The problem of selecting the power level at which a sensor should transmit is formulated as a Markov Decision Process (MDP) and the performance of the transmission policy thus derived is compared with that of an energy balancing policy as well as an aggressive policy. Our results show that the quality of coverage associated with the MDP formulation outperforms the other policies.