Matching Multi-Fractal Process Parameters Against Real Data Traffic

Document type: Conference Papers
Peer reviewed: Yes
Full text:
Author(s): Patrik Carlsson, Markus Fiedler, Arne A. Nilsson
Title: Matching Multi-Fractal Process Parameters Against Real Data Traffic
Translated title: Matchning av process parameter för multifraktala processer mot verklig data trafik
Conference name: RadioVetenskap och Kommunikation - RVK 02
Year: 2002
City: Stockholm
Organization: Blekinge Institute of Technology
Department: Department of Telecommunications and Signal Processing (Institutionen för telekommunikation och signalbehandling)
Department of Telecommunications and Signal Processing S-372 25 Ronneby
+46 455 38 50 00
Authors e-mail:,,
Language: English
Abstract: Recent analyses of real data/internet traffic indicate that data traffic exhibits long-range dependence as well as self-similar or multi-fractal properties. By using mathematical models of Internet traffic that share these properties we can perform analytical studies of network traffic. This gives us an opportunity to analyse potential bottlenecks and estimate delays in the networks.

Processes with multi-fractal properties can be modeled by multiplying the output of Markov Modulated Rate Processes (MMRP) [1] each defined by four parameters. The MMRP are easily used in stochastic fluid flow modeling. This model is also suited for analysis of other traffic types e.g. VoIP and thus, it allows for integration of different traffic types, i.e. time-sensitive voice traffic with best-effort data traffic. Using this model we can calculate performance parameters for each individual stream that enters the system/model.

In this paper we show how to construct a multi-fractal process that is matched to measured data from MMRP sub processes.
Summary in Swedish: Vi försöker matcha parametrar som hör till processer med multifraktala egenskaper. Vi försöker matcha mot verklig trafik.
Subject: Telecommunications\General
Telecommunications\Fluid Flow Models
Keywords: Multi-fractal traffic, fluid flow model, numerical analysis, performance evaluation