Energy-Efficient and Fast Data Collection in UAV-Aided Wireless Sensor Networks for Hilly Terrains

Energy-constrained sensor nodes are often deployed in remote, hilly, and hard-to-reach areas for civilian military purposes. In such wireless networks (WSNs), an unmanned aerial vehicle (UAV) can be used to collect data from the nodes. Low-altitude UAVs utilized reduce energy consumption of WSNs by optimizing collection position. this study, we designed energy-efficient fast (EFDC) scheme UAV-aided hilly with help a UAV as mule. First, proposed central bias hybrid distributed clustering algorithm grouping sensors. Then, applied modified tabu search optimize position collecting cluster. To achieve collection, developed traveling salesman problem derived positions solved it applying genetic algorithm. Based on our simulation results, EFDC outperforms conventional ones terms consumption, scalability, control overhead, delay, load balancing.