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arXiv 0902.1736cs.NI
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互联网流量的统计特征及其在抽样中的应用

On the Statistical Characterization of Flows in Internet Traffic with Application to Sampling

Yousra Chabchoub, Christine Fricker, Fabrice Guillemin, Philippe Robert

摘要:

本文提出了一种新的估计Internet中TCP流统计特性的方法。为此,定义了一组新的随机变量(称为可观测量)。当处理采样流量时,这些可观测量可以很容易地从采样数据中计算出来。通过采用一个方便的鼠标/大象二分法也依赖于流量,它示出了这些变量如何给出一个可靠的统计表示的数据包的数量在连续的时间间隔与适当的持续时间由大流量。一个数学框架的开发,以估计该方法的精度。作为一个应用程序,它示出了如何可以估计大TCP流的数量时,只有采样流量可用。对不同类型的IP网络收集的实验数据,所提出的算法进行了测试。

英文摘要:

A new method of estimating some statistical characteristics of TCP flows in the Internet is developed in this paper. For this purpose, a new set of random variables (referred to as observables) is defined. When dealing with sampled traffic, these observables can easily be computed from sampled data. By adopting a convenient mouse/elephant dichotomy also dependent on traffic, it is shown how these variables give a reliable statistical representation of the number of packets transmitted by large flows during successive time intervals with an appropriate duration. A mathematical framework is developed to estimate the accuracy of the method. As an application, it is shown how one can estimate the number of large TCP flows when only sampled traffic is available. The algorithm proposed is tested against experimental data collected from different types of IP networks.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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