Computing offloading in hierarchical aerial computing based on matching games

In unmanned aerial vehicle (UAV) networks, efficient and reliable cooperation among UAVs is crucial for enabling UAV-assisted internet of things (IoT) services. In this paper, we consider a hierarchical aerial computing framework composed of multiple UAVs that assume different network roles based on their capabilities, providing data collection and computation services for diverse IoT applications. We then formulate a task offloading problem subject to delay and resource constraints, taking into account the service revenue requirements and computational demands of different UAVs. The problem aims to meet the service demands of UAVs while satisfying multiple constraints related to task delay and resource availability, resulting in an integer programming problem that is challenging to solve. Considering the complexity of exhaustive search, we propose a matching game-based solution algorithm to obtain the optimal task offloading decision among UAVs and prove that the algorithm is stable. Simulation results show that the algorithm proposed in this paper outperforms the benchmark scheme in terms of service benefits.