移动边缘计算中的无人机群协同任务卸载策略研究

针对应急灾害中通信受限的场景，研究了基于移动边缘计算(mobile edge computing, MEC)的无人机群(unmanned aerial vehicles，UAV)协同任务卸载问题。在对系统通信过程和计算过程的延时与能耗分析的基础上，设计联盟效用函数和回报函数，并基于享乐博弈模型提出联盟分割形成算法。理论分析证明，该算法最终收敛于某个稳定的联盟分割。仿真结果表明，相比其他典型策略，提出的策略具有更低延时和能耗，能够提升用户服务体验、增加设备续航时间，解决通信受限问题。

Research on UAVs collaborative task offloading strategy based on mobile edge computing

For the scenario of limited communication in emergency disaster, the problem of collaborate task offloading of Unmanned Aerial Vehicles (UAV) based on Mobile Edge Computing (MEC) is studied. Based on the analysis of the delay and energy consumption of communication process and calculation process, the coalition utility function and the payback function are designed. Based on the hedonic game model, this paper proposes a coalition partition formation algorithm. Through theoretical analysis, the algorithm can converge to a stable coalition partition. Simulation results show that the proposed strategy has lower system delay and energy consumption than other typical strategies, thereby improving user service experience, increasing device life time, and solving the problem of limited communication.