<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.</p></abstract>

The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.

Advanced Models and Algorithms for Self-Similar IP Network Traffic Simulation and Performance Analysis

University of Rousse, 8, Studentska Street 7017, Rousse, Bulgaria

SUNY, Oneonta 324B Netzer Administration Bldg. Oneonta, NY 13820, USA

Journal of Electrical Engineering

The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar...

Advanced Models and Algorithms for Self-Similar IP Network Traffic Simulation and Performance Analysis

Publié en ligne: 07 juin 2011

Pages: 341 - 349

DOI: https://doi.org/10.2478/v10187-010-0053-0

Mots clés
communication networks, IP network traffic, long-range dependent self-similar processes, advanced generators of self-similar teletraffic

This content is open access.

Advanced Models and Algorithms for Self-Similar IP Network Traffic Simulation and Performance Analysis

Publié en ligne: 07 juin 2011

Pages: 341 - 349

DOI: https://doi.org/10.2478/v10187-010-0053-0

Mots cléscommunication networks, IP network traffic, long-range dependent self-similar processes, advanced generators of self-similar teletraffic

This content is open access.

Mots clés
communication networks, IP network traffic, long-range dependent self-similar processes, advanced generators of self-similar teletraffic