NDLI: Predictive bandwidth control for MPEG video: a wavelet approach for self-similar parameters estimation

Content Provider	IEEE Xplore Digital Library
Author	Yen-Chieh Ouyang Li-Bin Yeh
Copyright Year	2001
Description	Author affiliation: Dept. of Electr. Eng., Nat. Chung-Hsing Univ., Taichung, Taiwan (Yen-Chieh Ouyang)
Abstract	The measurements of various types of network traffic are found to exhibit self-similar characteristics. A key parameter characterizing self-similar processes is the Hurst parameter H, which is designed to capture the degree of self-similarity. In order to determine if a given time series exhibits self-similarity, a method is needed to estimate H for a given time series. We present an estimation tool by using the wavelet transform. An important feature of the wavelet-based tool is the conceptual and practical simplicity, consisting essentially in measuring the slope. Moreover, the Hurst parameter can be accurately estimated from the power-law behavior of the wavelet coefficients. We use an FIR multilayer network to predict the next incoming data, then we apply the wavelet-based tool to measure the Hurst parameters of the predicted data. Based on these Hurst parameters, we apply the Norros (see IEEE JSAC, vol.15, no.2, p.200-8, 1997) formula to estimate the bandwidth requirement for each predicted data. Finally, we utilize the random early detection (RED) algorithm to traffic congestion control based on the predictive bandwidth.
Starting Page	1551
Ending Page	1555
File Size	365859
Page Count	5
File Format	PDF
ISBN	0780370971
DOI	10.1109/ICC.2001.937180
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-06-11
Publisher Place	Finland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bandwidth Parameter estimation Communication system traffic control Traffic control Finite impulse response filter Nonhomogeneous media Telecommunication control Telecommunication traffic Resource management Quality of service
Content Type	Text
Resource Type	Article

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