Actor-Critic-based UAV-assisted data collection in the wireless sensor network

Wireless Sensor Network (WSN) is widely utilized in large-scale distributed unmanned detection scenarios due to its low cost and flexible installation. However, WSN data collection encounters challenges in scenarios lacking communication infrastructure. Unmanned aerial vehicle (UAV) offers a novel solution for WSN data collection, leveraging their high mobility. In this paper, we present an efficient UAV-assisted data collection algorithm aimed at minimizing the overall power consumption of the WSN. Firstly, a two-layer UAV-assisted data collection model is introduced, including the ground and aerial layers. The ground layer senses the environmental data by the cluster members (CMs), and the CMs transmit the data to the cluster heads (CHs), which forward the collected data to the UAVs. The aerial network layer consists of multiple UAVs that collect, store, and forward data from the CHs to the data center for analysis. Secondly, an improved clustering algorithm based on K-Means++ is proposed to optimize the number and locations of CHs. Moreover, an Actor-Critic based algorithm is introduced to optimize the UAV deployment and the association with CHs. Finally, simulation results verify the effectiveness of the proposed algorithms.