A framework for interpreting measurement over Internet

Kave Salamatian, S. Fdida
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引用次数: 9

Abstract

This paper introduces a methodology for interpreting measurement obtained over Internet. The paper is motivated by the fact that a large number of published papers in empirical networking analysis follow a generic framework that might be formalized and generalized to a large class of problem. The objective of this paper is to present an interpretation framework and to illustrate it by examples coming from the networking literature. The aim of the paper is rather to give to the researcher who is confronted to measurements coming from a network some guidelines on how to formalize the way to address interpretation of observations.The paper is based on the remark that interpretation is essentially a matter of relating observed effects to hidden causes. This problem might be formalized in its most general setting as an inverse statistical inference problem. The paper illustrates this inverse statistical problem in the context of two well-referred problems: interpretation of active measurement and network tomography. It shows that even if at first glance these two problems are different, the solution framework is the same. We will also give description about how to solve that inverse statistical inference problem by the EM method or the Bayesian framework.The framework provided in this paper is a powerful solution to address the complex problem of interpreting measurement over Internet and network modelling.
一个在互联网上解释测量的框架
本文介绍了一种解释互联网测量结果的方法。本文的动机是,大量发表的实证网络分析论文遵循一个通用框架,该框架可能被形式化并推广到一大类问题。本文的目的是提出一个解释框架,并通过来自网络文献的例子来说明它。本文的目的是给研究人员谁是面对来自网络的测量一些指导方针,如何形式化的方式来解决解释的观察。这篇论文是基于这样一种观点,即解释本质上是将观察到的结果与隐藏的原因联系起来的问题。这个问题在最一般的情况下可以形式化为一个逆统计推理问题。本文在两个相关问题的背景下说明了这个逆统计问题:主动测量的解释和网络断层扫描。它表明,即使乍一看这两个问题是不同的,但解决方案框架是相同的。我们还将描述如何通过EM方法或贝叶斯框架解决逆统计推理问题。本文提供的框架是解决通过互联网和网络建模解释测量的复杂问题的有力解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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