E-Cube: Energy-efficient UAV Trajectory Scheduling with Height and Speed Optimization

Unmanned Aerial Vehicles (UAVs) are increasingly used in data collection from IoT ground nodes (GNs) in different wild areas and scenarios, such as visiting GNs on electrical transmission towers along the mountains, or flood monitoring GNs on the banks along the rivers. However, limited battery capacity greatly restricts the performance of UAV in above applications. In this paper, we propose E-Cube, a UAV energy optimization scheme that jointly considers speed and height scheduling. E-Cube first decomposes the UAV spatial motion in terrain with altitude fluctuation into the horizontal plane and the vertical plane for energy efficient solutions. On the horizontal plane, E-Cube performs a Speed-Sensitive Trajectory Selection Algorithm (STSA), which is based on a practical energy model, to schedule the speed and select the distance accumulation trajectory. For the method on the vertical plane, an Altitude-Sensitive Trajectory Selection Algorithm (ATSA) is adapted to select the trajectory with the minimum height changes greedily based on the local information and then optimizes energy consumption for flight control by reducing speed varying based on the global information. E-Cube is evaluated through a series of experiments, and the results demonstrate that E-Cube can save as much as 25.1% energy consumption on average compared to existed approaches.