基于UAV的空地协同任务卸载策略研究

随着各行业对大批量信息处理需求的增加，移动边缘计算（Mobile Edge Computing, MEC）技术应运而生。而在陆地障碍较多、MEC服务器搭载不便的情况下，研究了一种无人机（Unmanned Aerial Vehicle, UAV）中继辅助用户卸载任务到基站的场景。针对该场景，提出了一种基于博弈论的最优任务卸载方法，通过联合优化任务卸载比例和卸载策略使得系统时延最小化。由于这两个变量之间相互耦合，因此将原优化问题转化为两个子问题求解。首先，在确定策略的情况下，证明了系统时延最小值存在的条件，得到了用户的最优卸载比例闭合解。然后，将原优化问题转化为任务分配问题，并建立博弈论模型。在证明了该模型存在纳什均衡（Nash Equilibrium,NE）的前提下，经过多次迭代，求解得到基于时延最小的用户任务卸载策略集。仿真结果表明：上述方法有效降低了全局计算时延，在时效性上优于其他一些常见的卸载方法。

Research of air-to-ground cooperative task offloading strategy based on UAV-assisted

Mobile edge computing (MEC) technology has emerged, as processing a tremendous amount of data information has gradually become an urgent need in various industries. In the case of many land obstacles and inconvenient installation of MEC servers, a scenario where unmanned aerial vehicles (UAVs) relay assist users to offload tasks to the base station is proposed. Aiming at this scenario, an optimal task offloading method based on game theory is presented. In order to minimize system delay, the task-offloading ratio and task-offloading strategy are jointly optimized. Since these two variables are coupled with each other, the original optimization problem is transformed into two sub-problems for solving. First, the conditions for the existence of the minimum system latency are proved under the determined strategy. Simultaneously, the closed-form expression of the optimal offloading ratio is given. Then, the optimization problem is transformed into a task assignment problem and a game theory model is developed. By proving the existence of Nash Equilibrium (NE) in this model, the set of user task offloading policies based on the minimum delay is given after several iterations. The simulation demonstrates that the global computation time delay is effectively reduced by the above method, which is better than some other common offloading methods in terms of timeliness.