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Wireless sensor networks are widely used for everything from border security to monitoring waterway pollution. Supplying energy for long term deployment is a main challenge in the applications of wireless sensor networks, as batteries are the primary energy source. Current wireless sensor networks deployed for long periods either require additional infrastructure, such as solar panels, or periodic maintenance. Our research lab has proposed a novel solution that uses a micro unmanned aerial vehicle (UAV) to wirelessly charge the sensor nodes and prolong the sensor network lifetime. Recent studies have shown that significant power can be transferred wirelessly over medium distances. As the UAV itself has a limited energy capacity, the challenge is how to charge the sensor nodes so that the sensor network lifetime can be maximized. We prove that the optimization problem is NP-Complete and propose a series of algorithms. The results show that the current UAV wireless power transfer system can prolong the sensor network lifetime by more than 50%. The algorithms are divided into three categories: complete knowledge, some knowledge and no knowledge of sensor network energy. As expected, the results indicate that the more information the algorithm can use, the better performance it can achieve. In addition, we identify the bottlenecks of the current system, such as the high energy consumption rate of hovering while charging, and provide guidance for future improvements.
Adviser: Carrick Detweiler