网络连接可靠性分析的非参数统计方法

D. Papadimitriou, D. Careglio
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引用次数: 1

摘要

面对使用参数模型和相应的统计方法建模网络可靠性时的计算复杂性,本研究采用Kaplan-Meier生存概率估计和平均累积函数等非参数统计方法来表征互联网路由路径的动态特性(特别是稳定性特性)及其与相应转发路径的关系。为量化这些属性提供系统的方法,目的是使互联网连接(也称为计算机网络中的可达性)的可靠性评估成为可能。研究Internet路由路径的动态特性(特别是稳定性特性)及其与转发路径的关系,主要有三个原因。第一种解释是,路由路径的时空特性的短暂但频繁的变化可能影响相应转发路径的性能和运行条件;因此,他们的可靠性。第二个原因是,当观察到可归因于互联网空间局部化部分的相同(子集)路径时,频繁的不稳定性可能表明底层物理拓扑更容易发生故障;因此,显示有限的可靠性。第三个结果来自日益增长的运营需求,即使用经过充分验证的统计分析来提供对互联网路由转发系统性能和运行条件的长期估计,该统计分析考虑了事件的复发和不稳定事件之间的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nonparametric statistical methods to analyze the internet connectivity reliability
Facing computational complexity when modeling network reliability by means of parametric models and corresponding statistical methods, in the present study, we apply nonparametric statistical methods, such as the Kaplan-Meier survival probability estimator and the mean cumulative function, to characterize the dynamic properties (in particular, the stability properties) of the Internet routing paths and their relationship with the corresponding forwarding path(s). Providing systematic methodology for quantifying these properties aims at enabling reliability assessment of the Internet connectivity (also referred to as reachability in computer networking). The motivation for studying the dynamic properties (in particular, the stability properties) of the Internet routing paths and their relationship to forwarding paths stems from three main reasons. The first translates the fact that transient but frequent changes in the spatio-temporal properties of routing paths may affect the performance and operating conditions of the corresponding forwarding paths; hence, their reliability. The second reason is that frequent instabilities when observed for the same (subset of) path(s) that can be attributed to a spatially localized portion(s) of the Internet may reveal that the underlying physical topology is more prone to failures; hence, showing limited reliability. The third results from the increasing operational need to provide for a longer term estimation of the Internet routing-forwarding system performance and operating conditions using well-proven statistical analysis accounting for recurrence of events and correlation between instability events.
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