On the characteristics of Internet traffic variability: spikes and elephants

Tatsuya Mori, R. Kawahara, Shozo Naito, Shigeki Goto
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引用次数: 47

Abstract

Analysing and modeling of traffic play a vital role in designing and controlling of networks effectively. To construct a practical traffic model that can be used for various networks, it is necessary to characterize aggregated traffic and user traffic. This paper investigates these characteristics and their relationship. Our analyses are based on a huge number of packet traces from five different networks on the Internet. We found that: (1) marginal distributions of aggregated traffic fluctuations follow positively skewed (non-Gaussian) distributions, which leads to the existence of "spikes", where spikes correspond to an extremely large value of momentary throughput; (2) the amount of user traffic in a unit of time has a wide range of variability; and (3) flows within spikes are more likely to be "elephant flows", where an elephant flow is an IP flow with a high volume of traffic. These findings are useful in constructing a practical and realistic Internet traffic model.
互联网流量变异性的特征:尖峰和大象
流量分析和建模对网络的有效设计和控制起着至关重要的作用。为了构建一个适用于各种网络的实用流量模型,有必要对聚合流量和用户流量进行表征。本文探讨了这些特征及其相互关系。我们的分析是基于来自互联网上五个不同网络的大量数据包痕迹。我们发现:(1)聚合流量波动的边际分布遵循正偏态(非高斯)分布,这导致“峰值”的存在,其中峰值对应于瞬时吞吐量的极大值;(2)单位时间内的用户流量具有较大的可变性;(3)峰值内的流量更有可能是“大象流”,其中大象流是具有高流量的IP流。这些发现对于构建一个实用的、现实的互联网流量模型是有用的。
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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