Path Planning Algorithm for a Hybrid Wireless Sensor Network and UAV as Mobile Sink Considering Energy Constraints

Wireless Sensor Networks (WSNs) play a crucial role in several applications ranging from precision agriculture to health wearable devices. A significant issue regarding WSN is energy consumption. To tackle this problem, clustering technique is frequently considered. In this context and according to the literature, the inclusion of a mobile sink node, such as an Unmanned Aerial Vehicle (UAV), can dramatically decrease energy consumption due to the communication, since the UAV can collect the data from the static nodes. This paper addresses this problem by modifying the A ^∗ path planning algorithm for a fixed-wing UAV considering wind field constraints. The position of the cluster heads is also optimized in the problem in order to further reduce the energy consumption of static network nodes and the flying data collector dynamic node. The results demonstrate that the modified A ^∗ algorithm and the deployed clustering technique efficiently find an optimal path with a gain in energy of up to 20% for the UAV and 25% for the network.