Abstract
This paper reviews the multifractal wavelet model (MWM) and its applications to network traffic modeling and inference. The discovery of the fractal nature of traffic has made new models and analysis tools for traffic essential, since classical Poisson and Markov models do not capture important fractal properties like multiscale variability and burstiness that deleteriously affect performance. Set in the framework of multiplicative cascades, the MWM provides a link to multifractal analysis, a natural tool to characterize burstiness. The simple structure of the MWM enables fast O(N) synthesis of traffic for simulations and a tractable queuing analysis, thus rendering it suitable for real networking applications including end-to-end path modeling.
Original language | English (US) |
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Title of host publication | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
Pages | 3429-3432 |
Number of pages | 4 |
Volume | 6 |
State | Published - 2001 |
Event | 2001 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing - Salt Lake, UT, United States Duration: May 7 2001 → May 11 2001 |
Other
Other | 2001 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing |
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Country/Territory | United States |
City | Salt Lake, UT |
Period | 5/7/01 → 5/11/01 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Signal Processing
- Acoustics and Ultrasonics