PoiRoot:调查域间路径改变的根本原因

Umar Javed, Ítalo F. S. Cunha, D. Choffnes, Ethan Katz-Bassett, T. Anderson, A. Krishnamurthy
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引用次数: 64

摘要

经常发生域间路径更改。由于路由协议暴露的信息不足以解释所有更改,因此确定根本原因的一般问题仍然没有解决。在这项工作中,我们设计并评估了PoiRoot,这是一个实时系统,允许提供商准确地隔离影响其前缀的路径变化的根本原因(负责的网络)。首先,我们开发了一个描述路径变化的新模型,并用它来证明所有可能负责的网络的集合。接下来,我们开发了一种递归算法,可以准确地分离任何路径更改的根本原因。我们观察到,该算法需要监控路径,而使用标准测量工具通常是不可见的。为了解决这个限制,我们以新的方式组合现有的度量工具,以获得隔离路径更改的根本原因所需的路径信息。我们通过受控的互联网实验、模拟和“野外”测量来评估PoiRoot的路径变化。我们证明了PoiRoot是高度准确的,即使只有部分信息也能很好地工作,并且通常会将根本原因缩小到一个或两个相邻的网络。在对照实验中,PoiRoot的准确率是100%,而之前的工作只有61.7%的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PoiRoot: investigating the root cause of interdomain path changes
Interdomain path changes occur frequently. Because routing protocols expose insufficient information to reason about all changes, the general problem of identifying the root cause remains unsolved. In this work, we design and evaluate PoiRoot, a real-time system that allows a provider to accurately isolate the root cause (the network responsible) of path changes affecting its prefixes. First, we develop a new model describing path changes and use it to provably identify the set of all potentially responsible networks. Next, we develop a recursive algorithm that accurately isolates the root cause of any path change. We observe that the algorithm requires monitoring paths that are generally not visible using standard measurement tools. To address this limitation, we combine existing measurement tools in new ways to acquire path information required for isolating the root cause of a path change. We evaluate PoiRoot on path changes obtained through controlled Internet experiments, simulations, and "in-the-wild" measurements. We demonstrate that PoiRoot is highly accurate, works well even with partial information, and generally narrows down the root cause to a single network or two neighboring ones. On controlled experiments PoiRoot is 100% accurate, as opposed to prior work which is accurate only 61.7% of the time.
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