Computing optimal drone positions to wirelessly recharge IoT devices

In an Internet of Things (IoT) environment such as the wireless sensor network the nodes are usually powered by batteries. When the nodes are deployed in a harsh environment the battery replacement may be a hard task or the cost of the maintenance may be very high. In this paper, we explore the possibility of recharging the nodes using drones equipped with chargers that can wirelessly transfer energy to the nodes. We examine the problem of minimizing the number of drone positions by adjusting the drones' altitude since the harvesting power is related to the altitude the drones fly. Indeed, the higher the altitude, the larger the observed area but the lower the harvesting power. The aim is to find the minimum possible drone locations such that all the nodes are charged before the drones run out of energy. We show that this problem can be reduced to the set-cover problem which is NP-Complete. We propose a time-efficient heuristic which can run on devices with low processing capabilities. We, also, solve the problem using Integer Linear Programming (ILP) capable of providing the optimal solution. The evaluation using a set of Monte Carlo simulations shows significant performance gains in terms of execution time compared to the ILP solution while keeping the number of positions close to the optimal.