Generation and Characterization of Self-Similar Teletraffic Using a New Model of Piecewise Affine Chaotic One-dimensional Map

EasyChair Preprint no. 5158

Abstract

This paper presents a qualitative and quantitative extension of the chaotic models used to generate and characterize self-similar traffic with long range dependence (LRD) in high-speed computer networks by means of the formulation of a new model that considers the use of piecewise affine (PWA) one-dimensional maps. Based on the disaggregation of the temporal series generated, an explanation of the behavior of the values of Hurst's exponent (H) is proposed and the feasibility of their control from the parameters of the proposed model is shown.

Keyphrases: chaotic maps, Hurst exponent (H), Long-Range Dependence (LRD), self-similarity, Teletraffic models

@Booklet{EasyChair:5158,
  author = {Ginno Millán},
  title = {Generation and Characterization of Self-Similar Teletraffic Using a New Model of Piecewise Affine Chaotic One-dimensional Map},
  howpublished = {EasyChair Preprint no. 5158},

  year = {EasyChair, 2021}}