Energy-Efficient UAV-Assisted IoT Data Collection via TSP-Based Solution Space Reduction
This work addresses energy-efficient data collection for IoT systems using UAVs, but it is incremental as it builds on existing TSP methods with a specific optimization.
This paper tackled the problem of optimizing a UAV's flight path to collect data from distributed IoT sensors by formulating it as a Traveling Salesman Problem variant, proving that optimal waypoints are restricted to sensor communication range boundaries to reduce solution space, and demonstrated energy savings in a use case.
This paper presents a wireless data collection framework that employs an unmanned aerial vehicle (UAV) to efficiently gather data from distributed IoT sensors deployed in a large area. Our approach takes into account the non-zero communication ranges of the sensors to optimize the flight path of the UAV, resulting in a variation of the Traveling Salesman Problem (TSP). We prove mathematically that the optimal waypoints for this TSP-variant problem are restricted to the boundaries of the sensor communication ranges, greatly reducing the solution space. Building on this finding, we develop a low-complexity UAV-assisted sensor data collection algorithm, and demonstrate its effectiveness in a selected use case where we minimize the total energy consumption of the UAV and sensors by jointly optimizing the UAV's travel distance and the sensors' communication ranges.