On the self-similar nature of Ethernet traffic
- 1 October 1993
- conference paper
- conference paper
- Published by Association for Computing Machinery (ACM)
- Vol. 23 (4), 183-193
- https://doi.org/10.1145/166237.166255
Abstract
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 such behavior has serious implications for the design, control, and analysis of high-speed, cell-based networks. Intuitively, the critical characteristic of this self-similar traffic is that there is no natural length of a "burst": at every time scale ranging from a few milliseconds to minutes and hours, similar-looking traffic bursts are evident; we find that aggregating streams of such traffic typically intensifies the self-similarity ("burstiness") instead of smoothing it.Our conclusions are supported by a rigorous statistical analysis of hundreds of millions of high quality Ethernet traffic measurements collected between 1989 and 1992, coupled with a discussion of the underlying mathematical and statistical properties of self-similarity and their relationship with actual network behavior. We also consider some implications for congestion control in high-bandwidth networks and present traffic models based on self-similar stochastic processes that are simple, accurate, and realistic for aggregate traffic.Keywords
This publication has 12 references indexed in Scilit:
- Statistics, Probability and ChaosStatistical Science, 1992
- Local area network characteristics, with implications for broadband network congestion managementIEEE Journal on Selected Areas in Communications, 1991
- Efficient Parameter Estimation for Self-Similar ProcessesThe Annals of Statistics, 1989
- A Markov Modulated Characterization of Packetized Voice and Data Traffic and Related Statistical Multiplexer PerformanceIEEE Journal on Selected Areas in Communications, 1986
- Large-Sample Properties of Parameter Estimates for Strongly Dependent Stationary Gaussian Time SeriesThe Annals of Statistics, 1986
- Fractional differencingBiometrika, 1981
- AN INTRODUCTION TO LONG‐MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCINGJournal of Time Series Analysis, 1980
- Some long‐run properties of geophysical recordsWater Resources Research, 1969
- Long-Run Linearity, Locally Gaussian Process, H-Spectra and Infinite VariancesInternational Economic Review, 1969
- Self-Similar Error Clusters in Communication Systems and the Concept of Conditional StationarityIEEE Transactions on Communications, 1965