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

Automated summary

The study presents an energy-efficient and fast data collection scheme for hilly areas using UAV-aided WSNs. By grouping sensors with a distributed clustering algorithm, optimizing UAV position with a modified tabu search algorithm, and solving the traveling salesman problem with a modified genetic algorithm, fast data collection is achieved. The proposed scheme outperforms conventional methods in terms of energy consumption, scalability, control overhead, delay, and load balancing based on simulation results.