Charge selection algorithms for maximizing sensor network life with UAV-based limited wireless recharging

Monitoring bridges with wireless sensor networks aids in detecting failures early, but faces power challenges in ensuring reasonable network lifetimes. Recharging select nodes with Unmanned Aerial Vehicles (UAVs) provides a solution that currently can recharge a single node. However, questions arise on the effectiveness of a limited recharging system, the appropriate node to recharge, and the best sink selection algorithm for improving network lifetime given a limited recharging system. This paper simulates such a network in order to answer those questions. It explores five different sink positioning algorithms to find which provides the longest network lifetime with the added capability of limited recharging. For a range of network sizes, our results show that network lifetime improves by over 350% when recharging a single node in the network, the best node to recharge is the one with the lowest power level, and that either the Greedy Heuristic or LP sink selection algorithms perform equally well.