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 …

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 …

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 …

Recent measurements of network traffic have shown that self-similarity is an ubiquitous
phenomenon present in both local area and wide area traffic traces. In previous work, we …

A number of recent empirical studies of traffic measurements from a variety of working
packet networks have convincingly demonstrated that actual network traffic is self-similar or …

In this article, we propose a new model for aggregate network traffic. This model, besides
reflecting self-similarity and long-range dependence, is able to capture the appropriate level …

We state and prove the following key mathematical result in self-similar traffic modeling: the
superposition of many ON/OFF sources (also known as packet trains) with strictly alternating …

There is much experimental evidence that network traffic processes exhibit ubiquitous
properties of self-similarity and long-range dependence, ie, of correlations over a wide …

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 …

A number of empirical studies of traffic measurements from a variety of working packet
networks have demonstrated that actual network traffic is self-similar or long-range …