Multi-objective NSGA-II optimization framework for UAV path planning in an UAV-assisted WSN

The recent technological advancements such as IoT-enabled sensor nodes, Global Positioning System, Wi-Fi transceivers, and lightweight lithium-ion batteries enable the use of Unmanned Aerial Vehicles (UAV) for data collection in wireless sensor networks. In a UAV-assisted wireless sensor network (UAV-WSN), the sensor nodes are installed at the ground and a UAV works as the sink node. The UAV-based sink flies over the sensed region and receives the data packets of surrounding ground nodes. A UAV-WSN offers improved data collection efficiency as the UAV-based sink avoids the ground obstacles and establishes line-of-sight communication with the ground sensor nodes. However, the UAV's flight trajectory needs to be optimized to achieve minimized UAV energy consumption during flight operation and minimized node energy consumption in data transmission. This paper presents a hybrid data routing protocol for UAV-WSN that considers optimized planning of the UAV's flight trajectory in parallel with energy-efficient data communication amid ground sensor nodes and the UAV. The presented scheme utilizes multi-objective NSGA-II optimization heuristics to optimize UAV's flight trajectory. The developed NSGA-II model evolves into an optimal UAV flight trajectory that simultaneously achieves the objectives of minimized UAV energy consumption, minimized node energy consumption, and maximized average RSSI. A maximized RSSI further brings about a significant increase in network throughput rate. Simulation results depict that the proposed UAV-WSN scheme achieves improved network lifetime and network throughput rate compared to other state-of-the-art protocols.