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Investigating the Scaling Behavior, Crossover and Anti-persistence of Internet Packet Delay Dynamics (1999)
| Venue: | IN PROCEEDINGS OF IEEE GLOBECOM'99, RIO DE JONERIO |
| Citations: | 9 - 1 self |
BibTeX
@INPROCEEDINGS{Li99investigatingthe,
author = {Qiong Li and David L. Mills},
title = {Investigating the Scaling Behavior, Crossover and Anti-persistence of Internet Packet Delay Dynamics },
booktitle = {IN PROCEEDINGS OF IEEE GLOBECOM'99, RIO DE JONERIO},
year = {1999},
pages = {1843--1852},
publisher = {}
}
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Abstract
Relying on the wavelet-based time-scale analysis techniques and a so called height difference correlation function method, we studied the dynamics of the delay traces measured in the Internet with sampling interval ranging from 20 ms to 1 min. Scaling analyses showed that the delay traces have a complicated scaling behavior changing with both the time scales and the sampling intervals. A significant observation of our research was that the nature of the delay traces changes from a LRD noise-like time series (e.g., fractional Brownian noise) to a self-similar one with an outer cutoff scale when the sampling intervals decrease (we refer this as crossover). It turns out that the delay jitter time series derived from a sampled delay trace with small sampling interval is LRD noise with a Hurst parameter H ! 0:5 (anti-persistence), indicating that the current Internet works in a controlled state. We also used a wavelet-based partition function method to investigate the possible multifractality of the delay traces. We analyzed the underlying physical mechanisms of the observed scaling behavior, crossover and anti-persistence, and discussed the implications of our findings on several aspects of networking engineering.
Keyphrases
scaling behavior internet packet delay dynamic delay trace lrd noise-like time series outer cutoff scale sampling interval decrease possible multifractality wavelet-based time-scale analysis technique sampling interval lrd noise wavelet-based partition function method underlying physical mechanism delay jitter time series delay trace change current internet work time scale sampled delay trace controlled state observed scaling behavior significant observation several aspect fractional brownian noise hurst parameter self-similar one
