A Prototyping Tool for Analysis and Modeling of Video Transmission Traces over IP Networks

Ming Yang, N. Bourbakis
{"title":"A Prototyping Tool for Analysis and Modeling of Video Transmission Traces over IP Networks","authors":"Ming Yang, N. Bourbakis","doi":"10.1109/RSP.2006.4","DOIUrl":null,"url":null,"abstract":"In the best-effort IP network, packet delay/loss is inevitably degrade the perceptual quality of real-time multimedia service, such as Voice-over-IP (VoIP), video-on-demand (VoD), etc. Modeling, prototyping, and analysis of traffic traces have always been very important and challenging topics in the area of multimedia communication. In general, packet loss/delay exhibits temporal dependence. Different prototyping tools, such as Bernoulli model, Gilbert model, Extended Gilbert model, Markov model, etc, have been proposed to model network trace. In this research, one VoD server and three clients have been setup to simulate a real VoD system. Different models have been applied to analyze and model the video transmission network traces obtained under RTP/UDP/IP protocol stack. Compared to the other tools, Markov model offers the best prototyping precision, in the sense of loss-run distribution and forward error correction (FEC) performance prediction. As a powerful fast prototyping tool, Markov model is very useful to model and analyze network traces and further improve the QoS in multimedia-over-IP","PeriodicalId":113937,"journal":{"name":"Seventeenth IEEE International Workshop on Rapid System Prototyping (RSP'06)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seventeenth IEEE International Workshop on Rapid System Prototyping (RSP'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RSP.2006.4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

In the best-effort IP network, packet delay/loss is inevitably degrade the perceptual quality of real-time multimedia service, such as Voice-over-IP (VoIP), video-on-demand (VoD), etc. Modeling, prototyping, and analysis of traffic traces have always been very important and challenging topics in the area of multimedia communication. In general, packet loss/delay exhibits temporal dependence. Different prototyping tools, such as Bernoulli model, Gilbert model, Extended Gilbert model, Markov model, etc, have been proposed to model network trace. In this research, one VoD server and three clients have been setup to simulate a real VoD system. Different models have been applied to analyze and model the video transmission network traces obtained under RTP/UDP/IP protocol stack. Compared to the other tools, Markov model offers the best prototyping precision, in the sense of loss-run distribution and forward error correction (FEC) performance prediction. As a powerful fast prototyping tool, Markov model is very useful to model and analyze network traces and further improve the QoS in multimedia-over-IP
IP网络上视频传输路径分析与建模的原型工具
在最佳努力的IP网络中,数据包的延迟/丢失不可避免地降低了实时多媒体业务的感知质量,如IP语音(VoIP)、视频点播(VoD)等。流量轨迹的建模、原型化和分析一直是多媒体通信领域中非常重要和具有挑战性的课题。一般来说,丢包/延迟表现出时间依赖性。不同的原型工具,如伯努利模型、吉尔伯特模型、扩展吉尔伯特模型、马尔可夫模型等,已被提出建模网络轨迹。本研究设置一个视频点播服务器和三个客户端来模拟一个真实的视频点播系统。采用不同的模型对RTP/UDP/IP协议栈下获得的视频传输网络轨迹进行分析和建模。与其他工具相比,马尔可夫模型在损失运行分布和前向纠错(FEC)性能预测方面提供了最好的原型精度。马尔可夫模型作为一种功能强大的快速原型工具,对网络轨迹的建模和分析以及进一步提高ip上多媒体的服务质量非常有用
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信