Fractal behavior and long-range dependence are widely observed in measurements and characterization of traffic flow in high-speed computer networks of different technologies and coverage levels. This paper presents the results obtained when applying fractal analysis techniques on a time series obtained from traffic captures coming from an application server connected to the Internet through a high-speed link. The results obtained show that traffic flow in the dedicated high-speed network link have fractal behavior when the Hurst exponent is in the range of 0.5, 1, the fractal dimension between 1, 1.5, and the correlation coefficient between -0.5, 0. Based on these results, it is ideal to characterize both the singularities of the traffic and its impulsiveness during a fractal analysis of temporal scales. Finally, based on the results of the time series analyses, the fact that the traffic flows of current computer networks exhibit fractal behavior with a long-range dependency is reaffirmed.

翻译：在对不同技术和覆盖水平的高速计算机网络的交通流量进行测量和定性时,广泛观察到分形行为和长距离依赖性。本文件介绍了在对从通过高速链接连接互联网的应用程序服务器上获取的交通量捕捉到的时间序列应用分形分析技术时取得的结果。获得的结果显示,专用高速网络链接的交通流量在赫斯特速度在0.5、1、1、1、1.5之间的分形维度和-0.5、0之间的相关系数之间时具有分形行为。根据这些结果,在对时间尺度进行分形分析时,最好既说明交通的奇特性,又说明其内性。最后,根据时间序列分析的结果,重申当前计算机网络的交通流量具有长期依赖性。