论文标题
在光学地铁网络上的延迟感知5G网络切片的演示
Demonstration of latency-aware 5G network slicing on optical metro networks
论文作者
论文摘要
H2020 Metro-Haul欧洲项目已经构建了一种潜伏,具有成本效益,敏捷和可编程的光学地铁网络。这包括具有具有计算和存储功能的半分散的地铁节点的设计,它们可以有效地与核心中的5G访问和多Tbit/s弹性光学网络接口。在本文中,我们报告了5G服务的自动部署,特别是使用相机和边缘分析的低延迟对象检测和跟踪的公共安全视频监视用例。该演示具有网络切片实例的灵活部署,该实例是根据欧洲电信标准研究所(ETSI)网络功能虚拟化网络服务实施的。我们在端到端服务质量,服务设置时间和软失败检测时间的详细分析中总结了关键发现。结果表明,80公里链接的往返时间低于800,服务部署时间不到180年代。
The H2020 METRO-HAUL European project has architected a latency-aware, cost-effective, agile, and programmable optical metro network. This includes the design of semidisaggregated metro nodes with compute and storage capabilities, which interface effectively with both 5G access and multi-Tbit/s elastic optical networks in the core. In this paper, we report the automated deployment of 5G services, in particular, a public safety video surveillance use case employing low-latency object detection and tracking using on-camera and on-the-edge analytics. The demonstration features flexible deployment of network slice instances, implemented in terms of European Telecommunications Standards Institute (ETSI) network function virtualization network services. We summarize the key findings in a detailed analysis of end-to-end quality of service, service setup time, and soft-failure detection time. The results show that the round-trip time over an 80 km link is under 800s and the service deployment time is under 180s.