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Shrink

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摘要

Faults in an IP network have various causes such as the failure of one or more routers at the IP layer, fiber-cuts, failure of physical elements at the optical layer, or extraneous causes like power outages. These faults are usually detected as failures of a set of dependent logical entities--the IP links affected by the failed components. We present Shrink, a tool for root cause analysis of network faults which, given a set of failed IP links, identifies the underlying cause of the faulty state. Shrink models the diagnosis problem as a Bayesian network. It has two main contributions. First, it effectively accounts for noisy measurement and inaccurate mapping between the IP and optical layers. Second, it has an efficient inference algorithm that finds the most likely failure causes in polynomial time and with bounded errors. We compare Shrink with two prior approaches and show that it substantially improves the performance.
机译:IP网络中的故障有多种原因,例如IP层上的一个或多个路由器发生故障,光纤中断,光学层上的物理元素发生故障或其他原因(例如断电)。通常将这些故障检测为一组相关逻辑实体的故障-受故障组件影响的IP链接。我们介绍了Shrink,这是一种用于分析网络故障的根本原因的工具,通过给出一组失败的IP链接,它可以识别故障状态的根本原因。 Shrink将诊断问题建模为贝叶斯网络。它有两个主要贡献。首先,它有效地解决了IP和光层之间的噪声测量和不准确的映射问题。其次,它具有高效的推理算法,可以找到多项式时间内最有可能的故障原因,并带有有限误差。我们将Shrink与两种先前的方法进行了比较,并表明它可以显着提高性能。

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