Modeling and performance evaluation of self-similar behavior of MPEG-4 video traffic generators

Variable bit rate (VBR) Moving Pictures Expert Group (MPEG) video is one of the major applications used on networks. Effective design and performance analysis of such networks thus depends on accurate modeling of MPEG video traffic. Recent studies of real traffic data in modern computer networks hav...

Full description

Saved in:

Bibliographic Details
Main Author:	Mohamed Abdelaziz, Izzeldin Ibrahim
Format:	Thesis
Language:	English
Published:	2006
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/3589/1/IzzeldinIbrahimMohamedPFKE2006.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-utm-ep.3589
record_format	uketd_dc
spelling	my-utm-ep.35892018-06-25T03:19:53Z Modeling and performance evaluation of self-similar behavior of MPEG-4 video traffic generators 2006-04 Mohamed Abdelaziz, Izzeldin Ibrahim TK Electrical engineering. Electronics Nuclear engineering Variable bit rate (VBR) Moving Pictures Expert Group (MPEG) video is one of the major applications used on networks. Effective design and performance analysis of such networks thus depends on accurate modeling of MPEG video traffic. Recent studies of real traffic data in modern computer networks have shown that traffic exhibits long-range dependence (LRD) properties over a wide range of time scales. The predominant way to quantify the long-range dependence is the value of the Hurst parameter, which shapes the autocorrelations of LRD processes, and it is needed for determining variance of such a process. Thus, correct and efficient estimation of the Hurst parameter is important in traffic analysis. There are several different methods to estimate the Hurst parameter, we have evaluated the most commonly used methods for estimating the self-similarity parameter H using appropriately long sequences of data. Estimators considered include, wavelet-based, R/S-statistic, variance-time, absolute-based and Periodogram-based. Our results have pointed to the wavelet-based estimator and R/S-based estimator as the most efficient estimators of the Hurst parameter. There is still a considerable debate about how to model the VBR video traffic. Many models have been proposed for the modeling of traffic sources. However, further work is required to verify their accuracy for modeling the MPEG video traffic. This thesis evaluates three different traffic source models, namely the Hosking-based model, the RMD-based model and chaotic mapbased model in terms of their statistical characteristics and to compare their outputs with the empirical traces to validate their effectiveness for modeling the MPEG-4 video traces. A comparison of the packet loss rate, queuing delay and throughput performance of RMD-based generator and chaotic-based generator with the performance of the real trace is used in validation of the models. Our simulation results show that the chaotic-based model capture the statistical characteristic of empirical traces better than Hosking-based and RMD-based models 2006-04 Thesis http://eprints.utm.my/id/eprint/3589/ http://eprints.utm.my/id/eprint/3589/1/IzzeldinIbrahimMohamedPFKE2006.pdf application/pdf en public phd doctoral Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Mohamed Abdelaziz, Izzeldin Ibrahim Modeling and performance evaluation of self-similar behavior of MPEG-4 video traffic generators
description	Variable bit rate (VBR) Moving Pictures Expert Group (MPEG) video is one of the major applications used on networks. Effective design and performance analysis of such networks thus depends on accurate modeling of MPEG video traffic. Recent studies of real traffic data in modern computer networks have shown that traffic exhibits long-range dependence (LRD) properties over a wide range of time scales. The predominant way to quantify the long-range dependence is the value of the Hurst parameter, which shapes the autocorrelations of LRD processes, and it is needed for determining variance of such a process. Thus, correct and efficient estimation of the Hurst parameter is important in traffic analysis. There are several different methods to estimate the Hurst parameter, we have evaluated the most commonly used methods for estimating the self-similarity parameter H using appropriately long sequences of data. Estimators considered include, wavelet-based, R/S-statistic, variance-time, absolute-based and Periodogram-based. Our results have pointed to the wavelet-based estimator and R/S-based estimator as the most efficient estimators of the Hurst parameter. There is still a considerable debate about how to model the VBR video traffic. Many models have been proposed for the modeling of traffic sources. However, further work is required to verify their accuracy for modeling the MPEG video traffic. This thesis evaluates three different traffic source models, namely the Hosking-based model, the RMD-based model and chaotic mapbased model in terms of their statistical characteristics and to compare their outputs with the empirical traces to validate their effectiveness for modeling the MPEG-4 video traces. A comparison of the packet loss rate, queuing delay and throughput performance of RMD-based generator and chaotic-based generator with the performance of the real trace is used in validation of the models. Our simulation results show that the chaotic-based model capture the statistical characteristic of empirical traces better than Hosking-based and RMD-based models
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Mohamed Abdelaziz, Izzeldin Ibrahim
author_facet	Mohamed Abdelaziz, Izzeldin Ibrahim
author_sort	Mohamed Abdelaziz, Izzeldin Ibrahim
title	Modeling and performance evaluation of self-similar behavior of MPEG-4 video traffic generators
title_short	Modeling and performance evaluation of self-similar behavior of MPEG-4 video traffic generators
title_full	Modeling and performance evaluation of self-similar behavior of MPEG-4 video traffic generators
title_fullStr	Modeling and performance evaluation of self-similar behavior of MPEG-4 video traffic generators
title_full_unstemmed	Modeling and performance evaluation of self-similar behavior of MPEG-4 video traffic generators
title_sort	modeling and performance evaluation of self-similar behavior of mpeg-4 video traffic generators
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2006
url	http://eprints.utm.my/id/eprint/3589/1/IzzeldinIbrahimMohamedPFKE2006.pdf
_version_	1747814456822333440

Modeling and performance evaluation of self-similar behavior of MPEG-4 video traffic generators

Similar Items