Modeling Self-Similar Traffic for Network Simulation

TL;DR

This paper discusses the importance of modeling self-similar traffic in networks to accurately simulate real-world scenarios and proposes a practical approach for generating such traffic traces with specified intensity.

Contribution

It introduces a method for modeling self-similar network traffic, addressing the need for realistic simulation of traffic flows in network research.

Findings

Self-similarity and long-range dependency are key properties of real network traffic.

A practical approach for generating self-similar traffic traces is proposed.

The method allows for specified traffic intensity in simulations.

Abstract

In order to closely simulate the real network scenario thereby verify the effectiveness of protocol designs, it is necessary to model the traffic flows carried over realistic networks. Extensive studies [1] showed that the actual traffic in access and local area networks (e.g., those generated by ftp and video streams) exhibits the property of self-similarity and long-range dependency (LRD) [2]. In this appendix we briefly introduce the property of self-similarity and suggest a practical approach for modeling self-similar traces with specified traffic intensity.