This invention discloses a joint optimization method and
system for task offloading and
resource allocation based on SAGIN. It collects task and scheduling information through a SAG-IoT
system; utilizes the task data and scheduling information to achieve optimal association between UAVs and IoT devices based on a
matching game algorithm, and makes optimal decisions for task offloading to maximize the computational performance of the SAG-IoT
system; based on optimal association, optimal task offloading decisions, and maximizing the computational performance of the SAG-IoT system, it constructs an online offloading framework based on deep
reinforcement learning, constructing a path from input X(t) to optimal action x. * The low-complexity mapping strategy (t) is based on repeated interactions between different modules and a random environment, iterating and running sequentially to achieve joint optimization of task offloading and
resource allocation. This invention achieves optimal computational performance while stabilizing the system
queue. In addition to utilizing binary computation offloading, the optimization framework can also be extended to online partial computation offloading strategies consisting of multiple independent subtasks.