arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1907.01293cs.NIcs.DC
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边缘基于服务的路由

Service-based Routing at the Edge

Dirk Trossen, Sebastian Robitzsch, Scott Hergenhan, Janne Riihijarvi, Martin Reed, Mays Al-Naday

摘要:

AR/VR等未来场景对5G的延迟和带宽要求提出了挑战。这种需求通过采用云原则来提供服务来补充,特别是用于虚拟化服务组件,其中虚拟化实例可以快速出现在网络中的不同执行点处。虽然提供接近最终用户的服务端点似乎很简单,但这种早期服务突破目前仅限于将请求路由到由客户网络深处的几个全球CDN参与者提供的接入点(POP)节点。在本文中,我们建议将互联网的边缘变成一个丰富的基于服务的路由基础设施,通过边缘计算节点提供服务,而不需要间接路由。我们的方法解释每一个基于IP的服务作为一个命名的服务(L2或类似的)传输网络,不需要在网络中的每流状态,同时原生支持单播和组播传输。该解决方案允许在几十毫秒的时间尺度内进行路由调整,从而实现快速故障恢复、响应速度极快的负载均衡、高效的移动性支持等。我们在基于标准SDN的基础设施和移动终端上以向后兼容的方式实施了我们的解决方案,从而实现了性能评估,该评估显示网络利用率和流建立时间有了显著改善。

英文摘要:

Future scenarios, such as AR/VR, pose challenging latency and bandwidth requirements in 5G. This need is complemented by the adoption of cloud principles for providing services, particularly for virtualizing service components with which virtualized instances can appear rapidly at different execution points in the network. While providing service endpoints close to the end user appears straightforward, this early service break-out is currently limited to routing requests to Point-of-Presence (POP) nodes provided by a few global CDN players deep in the customer network. In this paper, we propose instead to turn the edge of the Internet into a rich service-based routing infrastructure with services being provided through edge compute nodes, without needing indirect routing. Our approach interprets every IP-based service as a named service over a (L2 or similar) transport network, requiring no per-flow state in the network, while natively supporting both unicast and multicast delivery. The solution allows route adjustments in time scales of few tens of milliseconds, enabling rapid failure recovery, extremely responsive load balancing, efficient mobility support, and more. We implemented our solution on standard SDN-based infrastructure and in mobile terminals in a backwards-compatible manner, enabling a performance evaluation that shows significant improvements in network utilization as well as flow setup times.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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