System Cost Optimization-Based Task Offloading Algorithm in UAV-Assisted LEO Satellite Networks

In this work, we explore the task execution problem within unmanned aerial vehicle (UAV)-assisted low Earth orbit (LEO) satellite offloading networks. We define a system cost function that includes both energy consumption and task dropping cost, and formulate the joint power allocation, task offloading and scheduling, and UAV flight trajectory planning problem as a constrained system cost minimization problem. Given that the formulated problem is a mixed-integer nonlinear programming problem, which cannot be solved conveniently, we decompose the problem into four subproblems, i.e., IoT device task transmission subproblem, UAV trajectory design subproblem, power allocation subproblem, and task offloading and computing scheduling sub-problem. We propose an iterative algorithm for the first three subproblems and a heuristic for task offloading and computing scheduling subproblem. The simulation results reveal that our proposed method achieves superior performance compared to the existing algorithm.