Minimization of Aerial Cost and Mission Completion Time in Multi-UAV-Enabled IoT Networks

The application of unmanned aerial vehicles (UAVs) in IoT networks, especially data collection, has received extensive attention. Due to the urgency of the mission and limitation of the network cost, the mission completion time and number of UAVs are research hotspots. Most studies mainly focus on the trajectory optimization of the UAV to shorten the mission completion time. However, under different data collection modes, flying mode (FM) and hovering mode (HM), the collection time will also greatly affect the mission completion time. This paper studies the data collection from ground IoT devices (GIDs) in Multi-UAV enabled IoT networks. The problem of data collection is formulated to minimize the aerial cost and maximum mission completion time of UAVs by optimizing mission allocation, UAV trajectory, and UAVs' flying speeds. In view of the complexity and non-convexity of the formulated problem, we propose a heuristic-based approximation algorithm to optimize the mission allocation of UAVs. Then, we specifically optimize the trajectory of the UAV for GIDs to minimize the flight time and collection time. Since the UAV's flying speed affects the mission completion time, the successive convex approximation (SCA) technique is adopted to optimize it. Simulation results show that our scheme achieves the performance of near-optimal solution.