基于局部多尺度H参数估计的fGn和http请求跟踪分析

P. Głomb
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引用次数: 5

摘要

为了在实际应用中有效地利用流量模型,检测信号中嵌入的奇异点的能力非常重要。诸如每周模式变化、设备故障或节假日等事件都会影响信号特性,从而难以获得精确的交通参数。通过在不同尺度上进行局部分析,可以计算出估计参数的映射。本文提出了时间尺度估计H参数分解的概念(称为H面)和用于检测交通特征变化的方法。给出了基于合成fGn信号和http请求轨迹的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of fGn and http Requests Traces Using Localized Multiscale H Parameter Estimation
For effective employment of the traffic models in real applications, the ability to detect singularities embedded in the signal is very important. Events like weekly pattern variations, equipment malfunctions, or holiday periods affect signal characteristics, making it difficult to obtain precise traffic parameters. By performing analysis locally over different scales, a map of estimated parameters can be computed. This article presents a concept of time-scale estimated H parameter decomposition (called H surface) and methods applied to detect variations in the traffic characteristics. Results based on synthetic fGn signals and http requests traces are presented.
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