Joint Computation Offloading, UAV Trajectory, User Scheduling, and Resource Allocation in SAGIN

In this paper, we study the computation offloading problem in space-air-ground integrated networks (SAGIN), where joint optimization of partial computation offloading, unmanned aerial vehicles (UAVs) trajectory control, user scheduling, computation and resource allocation is performed. Specifically, the considered SAGIN employs multiple UAV-mounted edge servers with controllable UAV trajectory and a cloud sever which can be reached by ground users (GUs) via multi-hop low-earth-orbit (LEO) satellite communications. This design aims to minimize the weighted energy consumption of the GUs and UAVs while satisfying the maximum delay constraints of underlying computation tasks. To tackle the underlying non-convex mixed integer non-linear optimization problem, we use the alternating optimization approach where we iteratively solve five sub-problems, namely user scheduling, partial offloading control and bit allocation over time slots, computation resource, bandwidth allocation, and multi-UAV trajectory control until convergence. In addition, the successive convex approximation (SCA) method is employed to convexify and solve the non-convex bandwidth allocation and UAV trajectory control sub-problems. Via extensive numerical studies, we illustrate the effectiveness of our proposed design compared to baselines under different network settings.