fGn series to develop one-dimensional chaotic maps that generate self-similar LRD traffic on high-speed computer networks
A qualitative and quantitative extension of the chaotic models used to generate self-similar traffic with long-range dependence (LRD) is presented by means of the formulation of a model that considers the use of piecewise affine onedimensional maps. Based on the disaggregation of the temporal series generated, a valid explanation of the behavior of the values of Hurst exponent is proposed and the feasibility of their control from the parameters of the proposed model is shown.
fGn series used for simulations in the article "Sobre la Generación de Tráfico Autosimilar con Dependencia de Largo Alcance Empleando Mapas Caóticos Unidimensionales Afines por Tramos (Versión Extendida)", "On the Generation of Self-similar with Long-range Dependent Traffic Using Piecewise Affine Chaotic One-dimensional Maps (Extended Version)". Available at:
They should be used in MATLAB R2009a.
- MATLAB R2009a codes. 00 MATLAB R2009a Codes.zip (986 bytes)
- fGn series to develop one-dimensional chaotic maps that generate self-similar LRD traffic on high-speed computer networks. 01 fGn Series for Figures 1 to 10.zip (29.80 kB)
- MATLAB R2009a codes to generate figures 1 to 10. 02 Codes for Figures 1 to 10.zip (894 bytes)