Multi-UAV Data Collection Optimization for Sink Node and Trajectory Planning in WSN

Unmanned Areal Vehicles (UAVs) can be employed for temporary missions with flight ability while exposing limited flight energy and time due to restricted battery life. In this paper, to minimize the total energy consumption of both UAVs, the effective use of sink nodes’ power, we optimize both the number of sink nodes and the trajectories of multiple UAVs in WSN. In our scenario, all UAVs start their mission from the location of the charging station and back into the same charging station after finishing their data collection tasks. Specifically, we select the number of sink nodes using the Genetic Algorithm to maximize the lifetime WSN. The Multiple Traveling Salesman Problem (MTSP) based path planning algorithm is proposed to solve the trajectory using Held-Karp lower bound method for the trajectory path of UAV. The particle swarm optimization (PSO) and GA algorithm are demonstrated to get the feasible performance solution of the simulation results.