Computing Delay-Constrained Least-Cost Paths for Segment Routing is Easier Than You Think

Computing Delay-Constrained Least-Cost Paths for Segment Routing is Easier Than You Think
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DOI:
10.1109/nca51143.2020.9306706
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发表时间:
2020-11
期刊:
2020 IEEE 19th International Symposium on Network Computing and Applications (NCA)
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通讯作者:
Jean-Romain Luttringer;Thomas Alfroy;Pascal M'erindol;Quentin Bramas;F. Clad;C. Pelsser
Jean-Romain Luttringer;Thomas Alfroy;Pascal M'erindol;Quentin Bramas;F. Clad;C. Pelsser
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其他
文献类型:
--
作者:
Jean-Romain Luttringer;Thomas Alfroy;Pascal M'erindol;Quentin Bramas;F. Clad;C. Pelsser

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随着对实时视频流、云游戏和工业4.0应用等准即时通信服务需求的增长,多约束流量工程(TE)变得越来越重要。虽然传统TE管理平面的部署已被证明是费力的,但分段路由(SR)大大简化了TE路径的部署,因此成为许多运营商最合适的技术。SR的灵活性引发了对计算更复杂路径的需求。特别是,存在一个明确的需要,在计算和部署延迟约束最小成本路径(DCLC)的实时应用程序,需要低延迟和高带宽的路由。然而,目前大多数DCLC解决方案是专门为SR量身定制的算法。在这项工作中,我们利用延迟测量的准确性和SR增加的操作约束的固有限制。我们包括这些特点的BEST 2COP的设计,一个准确但有效的ECMP感知算法,本机解决DCLC在SR域。通过广泛的性能评估,我们首先表明,BEST2COP的规模,即使在大型随机网络。在具有多达数千个目的地的真实的网络中,我们的算法在不到一秒的时间内返回编码为SR路径的所有DCLC解决方案。
With the growth of demands for quasi-instantaneous communication services such as real-time video streaming, cloud gaming, and industry 4.0 applications, multi-constraint Traffic Engineering (TE) becomes increasingly important. While legacy TE management planes have proven laborious to deploy, Segment Routing (SR) drastically eases the deployment of TE paths and thus became the most appropriate technology for many operators. The flexibility of SR sparked demands in ways to compute more elaborate paths. In particular, there exists a clear need in computing and deploying Delay-Constrained Least-Cost paths (DCLC) for real-time applications requiring both low delay and high bandwidth routes. However, most current DCLC solutions are heuristics not specifically tailored for SR. In this work, we leverage both inherent limitations in the accuracy of delay measurements and an operational constraint added by SR. We include these characteristics in the design of BEST2COP, an exact but efficient ECMP-aware algorithm that natively solves DCLC in SR domains. Through an extensive performance evaluation, we first show that BEST2COP scales well even in large random networks. In real networks having up to thousands of destinations, our algorithm returns all DCLC solutions encoded as SR paths in way less than a second.