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Flow length and size distributions in campus Internet traffic

机译:校园互联网流量的流量长度和大小分布

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摘要

The efficiency of flow-based networking mechanisms strongly depends on traffic characteristics and should thus be assessed using accurate flow models. For example, in the case of algorithms based on the distinction between elephant and mice flows, it is extremely important to ensure realistic flows' length and size distributions. Credible models or data are not available in literature. Numerous works contain only plots roughly presenting empirical distribution of selected flow parameters, without providing distribution mixture models or any reusable numerical data. This paper aims to fill that gap and provide reusable models of flow length and size derived from real traffic traces. Traces were collected at the Internet-facing interface of the university campus network and comprise four billion layer-4 flow (275 TB). These models can be used to assess a variety of flow-oriented solutions under the assumption of realistic conditions. Additionally, this paper provides a tutorial on constructing network flow models from traffic traces. The proposed methodology is universal and can be applied to traffic traces gathered in any network. We also provide an open source software framework to analyze flow traces and fit general mixture models to them.
机译:基于流量的网络机制的效率强烈取决于交通特性,因此应使用精确的流量模型进行评估。例如,在基于大象和小鼠流动之间的区分的算法的情况下,确保现实流动的长度和尺寸分布非常重要。文献中不可用可信的模型或数据。许多作品仅包含粗略地呈现所选择的流量参数的经验分布,而不提供分发混合模型或任何可重复使用的数值数据。本文旨在填补该差距,并提供从真实流量迹线的流量长度和大小的可重用模型。在大学校园网络的互联网接口处收集迹线,包括四亿层 - 4流(275 TB)。这些型号可用于评估在现实条件的假设下进行各种面向的溶液。此外,本文提供了构建来自流量迹线的网络流模型的教程。所提出的方法是普遍的,可以应用于在任何网络中收集的交通迹线。我们还提供开源软件框架来分析流量迹线并将一般混合模型适合它们。

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