Estimating the Intensity of Long-Range Dependence in Real and Synthetic Traffic Traces

被引：0
|
作者：
Domanska, Joanna [1 ]
Domanski, Adam [2 ]
Czachorski, Tadeusz [1 ]
机构：
[1] Polish Acad Sci, Inst Theoret & Appl Informat, PL-44100 Gliwice, Poland
[2] Silesian Tech Univ, Inst Informat, PL-44100 Gliwice, Poland
来源：
COMPUTER NETWORKS, CN 2015 | 2015年 / 522卷
关键词：
Self-similarity; Long-range dependence; Hurst parameter; Fractional gaussian noise; Markov modulated poisson process; SELF-SIMILARITY; INTERNET; NOISES; MODELS;
D O I：
10.1007/978-3-319-19419-6_2
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper examines various techniques for estimating the intensity of Long-Range Dependence (LRD). Trial data sets with LRD are generated using Fractional Gaussian noise and Markov modulated Poisson process. The real data set collected in IITiS PAN is also used.
引用
收藏
页码：11 / 22
页数：12
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