To meet the demands for ubiquitous communication and temporary edge computing
in 6G networks, aerial mobile edge computing (MEC) networks have been
envisioned as a new paradigm. However, dynamic user requests pose challenges
for task assignment strategies. Most of the existing research assumes that the
strategy is deployed on ground-based stations or UAVs, which will be
ineffective in an environment lacking infrastructure and continuous energy
supply. Moreover, the resource mutual exclusion problem of dynamic task
assignment has not been effectively solved. Toward this end, we introduce the
digital twin (DT) into the aerial MEC network to study the resource coalition
cooperation approach with the generative model (GM), which provides a
preliminary coalition structure for the coalition game. Specifically, we
propose a novel network framework that is composed of an application plane, a
physical plane, and a virtual plane. After that, the task assignment problem is
simplified to convex optimization programming with linear constraints. And
then, we also propose a resource coalition cooperation approach that is based
on a transferable utility (TU) coalition game to obtain an approximate optimal
solution. Numerical results confirm the effectiveness of our proposed approach
in terms of energy consumption and utilization of resources.

利用数字孪生引入空中 MEC 网络，通过生成模型来研究资源联合合作方法，提出了一个由应用平面、物理平面和虚拟平面组成的新型网络框架，将任务分配问题简化为具有线性约束条件的凸优化规划，并提出基于可转让效用的联盟博弈来获取近似最优解，数值结果表明了我们提出方法在能源消耗和资源利用方面的有效性。