A Novel Genetic Model for Drone Positioning in Wireless Sensor Networks

Society is investing in Wireless Sensor Networks (WSN) in rural areas to protect the environment and agriculture while increasing security and enhance urban mobility in urban areas. In this context, Unmanned Aerial Vehicles (UAV) can be used for the collection of data recorded by sensors. However, the use of UAVs has introduced new challenges to be mitigated. In particular, in the WSN field, UAVs must follow strategies to increase the lifetime of the network, while also decrease the energy spent to realize the data transfer. Thus, in this work, we propose and evaluate a novel genetic algorithm considering the most important requirements listed in the literature. Experimental evaluations with different WSN setups show that the proposed genetic model is more effective in optimizing the network lifetime than classical strategies presented in the literature.