We consider a mobile edge computing (MEC) assisted Industrial Internet of Things (IIoT) network, where multiple assembly processing lines in a smart factory are equipped with sensing devices. They sense raw products, generate and offload computing tasks, and finally process the raw products based on the computing results. In this scenario, different positions of the processing machines lead to different priorities and diverse Quality-of-Service (QoS) requirements of tasks. Therefore, how to schedule tasks and allocate the network resources becomes a critical and challenging issue. In this study, we introduce a novel batch-based hybrid non-orthogonal multiple access (NOMA)/orthogonal multiple access (OMA) transmission scheme. The selection between NOMA and OMA schemes is optimized based on the QoS requirements of tasks. Then, we formulate a production efficiency maximization problem with the objective of maximizing the speed of the assembly lines subject to the deadline constraints of offloading and computing procedures. To this end, a two-layer decomposition method is used to decompose the formulated problem into two sub-problems. Furthermore, we utilize a bisection searching method to approximate the optimal solution, and propose an efficient method to determine the feasibility of the top-layer sub-problem. Simulation results demonstrate the significant performance improvement of our proposed method. In specific, the production efficiency is enhanced by 525% in comparison with pure NOMA scheme.

中文翻译：

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用于工业边缘计算网络生产效率最大化的混合 NOMA-OMA 传输调度


我们考虑移动边缘计算（MEC）辅助的工业物联网（IIoT）网络，其中智能工厂中的多条装配加工线都配备了传感设备。它们感知原始产品，生成并卸载计算任务，最后根据计算结果处理原始产品。在这种场景下，处理机的不同位置导致任务的优先级不同，服务质量（QoS）要求也不同。因此，如何调度任务和分配网络资源成为一个关键且具有挑战性的问题。在本研究中，我们引入了一种新颖的基于批量的混合非正交多址（NOMA）/正交多址（OMA）传输方案。根据任务的QoS要求，优化NOMA和OMA方案的选择。然后，我们制定了生产效率最大化问题，其目标是在卸载和计算程序的期限限制下最大化装配线的速度。为此，使用两层分解方法将公式化的问题分解为两个子问题。此外，我们利用二分搜索方法来逼近最优解，并提出了一种有效的方法来确定顶层子问题的可行性。仿真结果证明了我们提出的方法的显着性能改进。具体来说，生产效率比纯NOMA方案提高了525%。