Nowadays, the Internet of Video Things (IoVT) is growing rapidly in terms of quantity and computation demands. In spite of the higher local computation capability on visual processing compared to conventional Internet of Things devices, IoVT devices need to offload partial visual processing tasks to the mobile edge computing (MEC) server wirelessly due to its larger computation demands. However, visual processing task offloading is limited by uplink throughput and computation capability of the MEC server. To break through these limitations, a novel non-orthogonal multiple access (NOMA)-assisted IoVT framework with multiple MEC servers is proposed, where NOMA is exploited to improve uplink throughput, and MEC servers are co-located with base stations to provide enough computation capability for off-loading. In the proposed framework, the association strategy, uplink visual data transmission assisted by NOMA, and division of the visual processing tasks as well as computation resource allocation at the MEC servers are jointly optimized to minimize the total delay of all visual processing tasks, while meeting the delay requirements of all IoVT devices. Simulation results demonstrate that significant performance gains can be achieved by proposed joint optimization with NOMA transmission and multi-MEC offloading in the heterogeneous IoVT network.

中文翻译：

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用于 IoVT 网络的 NOMA 辅助多 MEC 卸载

如今，视频物联网（IoVT）在数量和计算需求方面都在快速增长。尽管与传统物联网设备相比，视觉处理的本地计算能力更高，但 IoVT 设备由于其更大的计算需求，需要将部分视觉处理任务无线卸载到移动边缘计算 (MEC) 服务器。然而，视觉处理任务卸载受到 MEC 服务器的上行吞吐量和计算能力的限制。为了突破这些限制，提出了一种具有多个 MEC 服务器的新型非正交多址 (NOMA) 辅助 IoVT 框架，其中利用 NOMA 来提高上行链路吞吐量，并且 MEC 服务器与基站共存以提供足够的计算卸载能力。在拟议的框架中，关联策略、NOMA辅助上行视觉数据传输、视觉处理任务的划分以及MEC服务器的计算资源分配共同优化，以最小化所有视觉处理任务的总延迟，同时满足所有视觉处理任务的延迟要求。物联网设备。仿真结果表明，在异构 IoVT 网络中，通过提出的与 NOMA 传输和多 MEC 卸载的联合优化可以实现显着的性能提升。