Dynamic Mobile Charger Scheduling in Heterogeneous Wireless Sensor Networks

Recent advances in energy transfer technology is boosting the development of renewable sensor networks. To sustain such a network, a mobile robot travels from node to node to recharge each sensor before its battery runs out. To solve this problem, we propose a spatial dependent task scheduling algorithm, which quantifies the impact of scheduling proximate tasks on the other tasks. Our evaluation results show that our algorithms out-perform classical TSP scheduler by up to10% and 85% in terms of coverage ratio and average tardiness, respectively.