了解域间路由动态的第一步

Kuai Xu, J. Chandrashekar, Zhi-Li Zhang
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引用次数: 37

摘要

BGP更新是由各种事件触发的,如链路故障、复位、路由器崩溃、配置变化等。理解这些更新并识别底层事件是调试和排除BGP路由问题的关键。在本文中,作为解决BGP更新的根本原因分析这一更为困难的问题的第一步,我们讨论了由不同底层事件触发的更新是否可以分离,以及如何分离。具体来说,我们探索使用PCA(主成分分析),一种众所周知的统计多变量技术,来实现这一目标。提出了一种基于PCA的从BGP更新流中获取聚类集的方法;其中每一个都是受相同底层事件影响的一组实体(前缀或ase)。然后用仿真得到的BGP数据验证了该方法的有效性。此外,我们还对包含众所周知的大规模事件的BGP数据进行高级分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A first step toward understanding inter-domain routing dynamics
BGP updates are triggered by a variety of events such as link failures, resets, routers crashing, configuration changes, and so on. Making sense of these updates and identifying the underlying events is key to debugging and troubleshooting BGP routing problems. In this paper, as a first step toward the much harder problem of root cause analysis of BGP updates, we discuss if, and how, updates triggered by distinct underlying events can be separated. Specifically, we explore using PCA (Principal Components Analysis), a well known statistical multi-variate technique, to achieve this goal.We propose a method based on PCA to obtain a set of clusters from a BGP update stream; each of these is a set of entities (either prefixes or ASes) which are affected by the same underlying event. Then we demonstrate our approach using BGP data obtained by simulations and show that the method is quite effective. In addition, we perform a high level analysis of BGP data containing well known, large scale events.
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