Optimization of Wireless Sensor Network and UAV Data Acquisition

This paper deals with selection of sensor network communication topology and the use of Unmanned Aerial Vehicles (UAVs) for data gathering. The topology consists of a set of cluster heads that communicate with the UAV. In conventional wireless sensor networks Low Energy Adaptive Clustering Hierarchy (LEACH) is commonly used to select cluster heads in order to conserve energy. Energy conservation is far more challenging for large scale deployments. Particle Swarm Optimization (PSO) is proposed as an optimization method to find the optimal topology in order to reduce the energy consumption, Bit Error Rate (BER), and UAV travel time. PSO is compared to LEACH using a simulation case and the results show that PSO outperforms LEACH in terms of energy consumption and BER, while the UAV travel time is similar. The numerical results further illustrate that the performance gap between them increases with the number of cluster head nodes. Because of reduced energy consumption, network life time can be significantly extended while increasing the amount of data received from the entire network. By considering the wind effect into the PSO scheme, it is shown that this has an impact on the traveling time for the UAV but BER and energy consumption are not significantly increased.