Joint Communication Topology Formation and Task Offloading for Heterogeneous UAV Swarms
The rapid evolution of swarm intelligence and edge computing has highlighted the potential of Uncrewed Aerial Vehicle (UAV) swarms for data-driven services. However, heterogeneous capabilities and time-varying communication conditions pose significant challenges for efficient resource orchestration. This letter proposes a novel method for joint communication topology formation and computation offloading in heterogeneous UAV networks to optimize task completion time and energy consumption. A graph attention network is employed for swarm feature extraction, and the communication topology and task offloading ratios are determined by proximal policy optimization. Successive convex approximation is further applied for bandwidth and power allocation. Simulation results demonstrate that the proposed framework effectively reduces task completion time and energy consumption compared with other benchmarks.