Energy Efficient and Balanced Task Assignment Strategy for Multi-AAV Patrol Inspection System in Mobile Edge Computing Network

This paper considers a patrol inspection scenario where multiple autonomous aerial vehicles (AAVs) are adopted to traverse multiple predetermined cruise points for data collection. The AAVs are connected to cellular networks and they would offload the collected data to the ground base stations (GBSs) for data processing within the constrained duration. This paper proposes a balanced task assignment strategy among patrol AAVs and an energy-efficient trajectory design method. Through jointly optimizing the cruise point assignment, communication scheduling, computational allocation, and AAV trajectory, a novel solution can be obtained to balance the multiple AAVs' task completion time and minimize the total energy consumption. Firstly, we propose a novel clustering method that considers geometry topology, communication rate, and offload volume; it can determine each AAV's cruise points and balance the AAVs' patrol task. Secondly, a hybrid Time-Energy traveling salesman problem is formulated to analyze the cruise point traversal sequence, and the energy-efficient AAV trajectory can be designed by adopting the successive convex approximation (SCA) technique and block coordinate descent (BCD) scheme. The numerical results demonstrate that the proposed balanced task assignment strategy can efficiently balance the multiple AAVs' tasks. Moreover, the min-max task completion time and total energy consumption performance of the proposed solution outperform that of the current conventional approach.