Joint Clustering and UAV Trajectory Planning Algorithm in UAV-Assisted WSNs with Data Collection Time Minimization

Unmanned aerial vehicle (UAV) has been considered as an efficient solution to collect data from wireless sensor networks (WSNs) due to its flexibility and mobility. In this paper, we consider a UAV-assisted WSN, wherein the UAV starts from directly above the sink node to collect data and returns to the initial position. To improve data collection performance, sensor node (SN) can be clustered and the cluster head (CH) is responsible for collecting data of cluster members (CMs) and forwarding the data to the sink node. Two data forwarding modes are considered, i.e., the direct transmission mode from CH to the sink node, and the UAV collection mode from CH to UAV and then to the sink node. A data collection time minimization problem is formulated, where the clustering strategy, CH transmission mode selection, UAV trajectory and UAV velocity are jointly optimized. To solve this non-convex problem, a modified K-means algorithm-based clustering scheme is proposed firstly. Based on which, a CH transmission mode selection strategy is designed, and then a traveling salesman problem (TSP)-based UAV trajectory planning algorithm is proposed. Numerical results demonstrate the effectiveness of the proposed algorithm.