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 …

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 …

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 …

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 …

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 …

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 …

Demonstrates that Ethernet LAN traffic is statistically self-similar, that none of the commonly
used traffic models is able to capture this fractal-like behavior, that such behavior has …

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 …

High-resolution traffic measurements from modern communications networks provide
unique opportunities for developing and validating mathematical models for aggregate …

This paper addresses the question of whether self-similar processes are sufficient to model
packet network traffic, or whether a broader class of multifractal processes is needed. By …