Towards Green Communication in UAV-Assisted Wireless Sensor Network

Unmanned Aerial Vehicle (UAV)-assisted Wireless Sensor Networks (WSN) enhance the effectiveness of smart city applications by providing comprehensive, real-time data collection capabilities that contribute to better urban planning, resource management, and disaster response. The need for energy-optimized routing in UAV-assisted WSNs for smart city applications is a big problem that needs to be solved by creating unique routing algorithms that can balance energy efficiency, real-time adaptability, and scalability to meet the specific needs of cities. In this work, we present an optimized Cluster-Head (CH) selection using Golden Jackal Optimization (GJO) by utilizing parameters, namely, node energy levels, node-to-sink distance, neighboring node density, and energy consumption rate. The network is three-level energy-heterogeneous for enhancing the network lifetime. The proposed work is suitable for smart city applications, namely Intelligent Transportation Systems, Landslide Detection, Wildfire Detection, etc., wherein the sensor nodes need to have optimized routing. The simulation analysis is done in MATLAB software wherein the proposed work i.e., GJO-based Routing Optimized for UAV-assisted WSN (GROW) outperforms the recently proposed routing frameworks on different benchmarks of performance measures (16% and 19% improvement over the stability period and network lifetime).