Unmanned aerial vehicles (UAVs) and communication systems are fundamental elements in Mission Critical services, such as search and rescue. In this article, we introduce an architecture for managing and orchestrating 5G and beyond networks that operate over a heterogeneous infrastructure with UAVs' aid. UAVs are used for collecting and processing data, as well as improving communications. The proposed System Intelligence (SI) architecture was designed to comply with recent standardization works, especially the ETSI Experiential Networked Intelligence specifications. Another contribution of this article is an evaluation using a testbed based on a virtualized non-standalone 5G core and a 4G Radio Access Network (RAN) implemented with open-source software. The experimental results indicate, for instance, that SI can substantially improve the latency of UAV-based services by splitting deep neural networks between UAV and edge or cloud equipment. Other experiments explore the slicing of RAN resources and efficient placement of virtual network functions to assess the benefits of incorporating intelligence in UAV-based mission-critical services.
翻译:无人驾驶航空飞行器(无人驾驶飞行器)和通信系统是任务关键服务(如搜索和救援)的基本内容。在本条中,我们引入了管理和指挥5G网络和网络以外的结构,这些网络在无人驾驶飞行器的协助下运作于一个多式基础设施,无人驾驶飞行器用于收集和处理数据,并改进通信。拟议的系统情报架构旨在遵守最近的标准化工作,特别是ETSI业务网络情报规格。本文章的另一个贡献是利用虚拟化的非独立5G核心和4G无线电接入网络(RAN)的测试台进行评价,这些测试台是使用开放源软件执行的4G无线电接入网络(RAN),实验结果显示,例如,SI通过将无人驾驶飞行器和边缘或云层设备之间的深层神经网络分割,可以大大改善以无人驾驶飞行器为基础的服务。其他实验探索了RAN资源的分层和虚拟网络功能的有效放置,以评估将情报纳入以无人驾驶飞行器为基础的任务关键服务的好处。