在即将到来的第六代移动通信技术（6G）时代，广域时延敏感物联网（IoT）需求不断增加。由于传统蜂窝技术难以直接用于广域时延敏感IoT，因此使用非地面基础设施，包括卫星和无人机（UAV）等，基于无蜂窝网络架构构建非地面网络（NTN）亟待研究。考虑到时延敏感业务需求和IoT 设备分布不均的特点，NTN可使用移动边缘计算（MEC）来增强业务支持能力，并提供'沙漠绿洲'状（oasis-oriented）的按需覆盖。然而，在MEC使能的NTN中，通信和MEC系统相互耦合，带来通信与计算资源协同编排难题。本文提出一种面向过程的优化框架，在更大时间尺度上设计通信和MEC系统。在这个框架中，本研究采用大尺度信道状态信息（CSI）刻画复杂传播环境，构建通信与计算资源联合编排的时延最小化问题；给出该优化问题的近似问题，并将其分解为多个子问题；然后，提出迭代算法来求解这些子问题。仿真结果表明，与现有算法相比，所提出的面向过程的方案可以降低任务总时延。这为无人机载荷部署提供了依据，也显示了在广域时延敏感IoT中NTN与MEC协同设计的潜力。

In the upcoming sixth-generation (6G) era, the demand for constructing a wide-area time-sensitive Internet of Things (IoT) continues to increase. As conventional cellular technologies are difficult to directly use for wide-area time-sensitive IoT, it is beneficial to use non-terrestrial infrastructures, including satellites and unmanned aerial vehicles (UAVs). Thus, we can build a non-terrestrial network (NTN) using a cell-free architecture. Driven by the time-sensitive requirements and uneven distribution of IoT devices, the NTN must be empowered using mobile edge computing (MEC) while providing oasisoriented on-demand coverage for devices. Nevertheless, communication and MEC systems are coupled with each other under the influence of a complex propagation environment in the MEC-empowered NTN, which makes it difficult to coordinate the resources. In this study, we propose a process-oriented framework to design communication and MEC systems in a time-division manner. In this framework, large-scale channel state information (CSI) is used to characterize the complex propagation environment at an affordable cost, where a nonconvex latency minimization problem is formulated. Subsequently, the approximated problem is provided, and it can be decomposed into sub-problems. These sub-problems are then solved iteratively. The simulation results demonstrated the superiority of the proposed process-oriented scheme over other algorithms, implied that the payload deployments of UAVs should be appropriately predesigned to improve the efficiency of using resources, and confirmed that it is advantageous to integrate NTN with MEC for wide-area time-sensitive IoT.