Average Transmission Rate and Energy Efficiency Optimization in UAV-assisted IoT

Internet of Things (IoT) has gradually been applied to various fields, including industries and agriculture, and plays an increasingly important role in society. However, the limited coverage of terrestrial IoT network restricts the communication performance of IoT devices, making the network inefficient. Unmanned aerial vehicles (UAVs) have the potential to be an efficient solution to improve the communication efficiency of the terrestrial IoT devices. Thus, we formulate a UAV-assisted data collection multi-objective optimization problem (UAVDCMOP) to jointly maximize the average transmission rate, minimize the total time of UAVs, and minimize the average energy consumed by UAVs via determining the optimal positions of UAVs. To this end, we propose an improved multi-objective grey wolf-based optimization (IMOGWO) algorithm with chaotic mapping initialization operator and inversion opposition generation operator, making it suitable for optimizing the formulated UAVDCMOP. Simulation results demonstrate that the proposed approach contributes to enhance the system average transmission rate and energy efficiency, and it has superior performance compared to other approaches.