UAV-assisted WSN Energy Saving Algorithm Based on Sparrow Search Optimized SFCM

UAV technology based on IoT, 5G and artificial intelligence is developing rapidly nowadays, and Unmanned aerial vehicles (UAV) are used in a variety of scenarios. In this paper, we study UAV-assisted wireless sensor networks (WSNs), in which UAVs receive data sent by sensors from data receiving points (RPs) and plan the path for UAVs to collect data at all RPs. The paper goal is to minimize the total energy consumption of the UAV-WSN system throughout the data collection process, while balancing the network energy consumption of the WSN and extending the network lifetime of the WSN. In this paper, propose the ISFSSA algorithm to initialize the election of RP, optimize the acquisition path, and dynamically update the RP based on the remaining SN energy and UAV acquisition angle. Simulation results show that compared with the SFSSA algorithm, CS-K algorithm, and PSO-K algorithm, the performance of balancing the WSN network energy consumption is improved by 3.5%, 19.3%, and 28.7%, and the performance of extending the network lifetime improved by 3.8%, 18.1%, and 28.3%, in addition, the ISFSSA algorithm has a significant performance advantage in reducing system energy consumption.