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Multi-fractal analysis of IP-network traffic for assessing time variations in scaling properties

机译:IP网络流量的多分形分析,以评估缩放属性的时间变化

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This paper presents a multi-fractal-based analysis of IP-network traffic in terms of the time variations in scaling properties. To obtain a comprehensive view in analyzing the scaling properties of IP-network traffic, we used a self-organizing map, which is an effective tool to map high-dimensional data onto a low-dimensional domain. Based on sequential measurements of IP-network traffic at two locations, we checked time variations in multi-fractal-based properties of measured data sets. In performing the self-organizing map-based analysis, we used three parameters: the highest value and the range of generalized fractal dimensions and the network throughput of measured network traffic. We visually confirmed that measured data sets could be classified and mapped in accordance with the network traffic properties, resulting in the combined depiction of the multi-fractal-related properties and network throughput, which can give us an effective assessment of network conditions at different times. (c) 2006 Elsevier B.V. All rights reserved.
机译:本文就缩放属性的时间变化提出了基于多分形的IP网络流量分析。为了获得分析IP网络流量的扩展属性的全面视图,我们使用了自组织映射,这是将高维数据映射到低维域的有效工具。基于在两个位置对IP网络流量的顺序测量,我们检查了测量数据集基于多分形的属性中的时间变化。在执行基于自组织图的分析时,我们使用了三个参数:最大值和广义分形维数的范围以及所测得网络流量的网络吞吐量。我们在视觉上确认可以根据网络流量属性对测得的数据集进行分类和映射,从而得出与多重分形相关的属性和网络吞吐量的组合描述,从而可以有效地评估不同时间的网络状况。 (c)2006 Elsevier B.V.保留所有权利。

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