The recent discovery of scaling phenomena in modern communication networks involving
self-similarity or fractals and power-law or heavy-tailed distributions is yet another realization …

There has been significant progress in developing appropriate mathematical and statistical
techniques that provide a physical‐based, networking‐related understanding of the …

Since the seminal study of Leland, Taqqu, Willinger, and Wilson, which set the groundwork
for considering self‐similarity an important notion in the understanding of network traffic …

This paper provides a bibliographical guide to researchers and tra c engineers who are
interested in self-similar tra c modeling and analysis. It lists some of the most recent network …

Traffic modeling of today's communication networks is a prime example of the role statistical
inference methods for stochastic processes play in such classical areas of applied …

We demonstrate that Ethernet local area network (LAN) traffic is statistically self-similar, that
none of the commonly used traffic models is able to capture this fractal behavior, and that …

We demonstrate that Ethernet local area network (LAN) traffic is statistically self-similar, that
none of the commonly used traffic models is able to capture this fractal behavior, and that …

Observations of both Ethernet traffic and variable bit rate (VBR) video traffic have
demonstrated that these traffics exhibit" self-similarity" and/or infinite asymptotic index of …

In this paper, we report on some preliminary results from an in-depth, wavelet-based
analysis of a set of high-quality, packet-level traffic measurements, collected over the last 6-7 …

The theory of stochastic networks is an important and rapidly developing research area,
driven in part by industrial applications in the design and control of modern communications …