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A Real-Time Multimedia Data Transmission Rate Control Using Neural Network Prediction Model  

Kim, Yong-Seok (삼성전자 Mobile R&D)
Kwon, Bang-Hyun (전북대학교 네트워크 시스템 제어연구실)
Chong, Kil-To (전북대학교 전자정보공학부)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.30, no.2B, 2005 , pp. 44-52 More about this Journal
Abstract
This paper proposes a neural network prediction model to improve the valid packet transmission rate for the QoS(Quality of Service) of multimedia transmission. The Round Trip Time(RTT) and Packet Loss Rate(PLR) are predicted using a neural network and then the transmission rate is decided based on the predicted RTT and the PLR. The suggested method will improve the transmission rate since it uses the rate control factors corresponding to time of data is being transmitted, while the conventional one uses the transmission rate determined based on the past informations. An experimental set-up has been established using a Linux PC system, and the multimedia data are transmitted using UDP protocol in real time. The valid transmitted packets are about 5% higher than the one in the conventional TCP-Friendly congestion control method when the suggested algorithm was applied.
Keywords
Multimedia Date Transmission; Neural Network; TCP; UDP;
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1 Joerg Widmer, Robert Denda, and Martin Mauve, Parkische Informatic IV, A Survey on TCP-Friendly Congestion Control, IEEE Network, vol. 3, pp.28-37, May/June, 2001
2 Ik Jun Yeom, 'ENDE: An End-To-End Network Delay Emulator', Master Thesis, Texas A&M University, 1998
3 W.Zhu, Q.Zhang and Y.-Q. Zhang, 'Network-adaptive rate control with unequal loss protection for scalable video over the internet. in Proceeding of IEEE International Symposium on Circuits and Systems 2001, vol. 5, pp. 109-112
4 F. Rosenblatt, 'The perception a probabilistic model for information storage and organization in the brain', Psychol. Rev. vol. 65, pp356-408, 1958
5 D. Wu, Y.T.Hou, W.Zhu, H.J.Lee, T.Chiang, Y.Q.Zhang, and H.J Chao, 'On end-to-end architecture for transporting MPEG-4 video over the Internet,' IEEE Trans. Circuits Syst. Video Technology vol. 10, pp 923-941, Sept. 2000   DOI   ScienceOn
6 J. Nie and D.A. Linkens, 'Fuzzy-Neural Control: Principles, Algorithms and Applications', pp. 203-220, Prentice Hall, 1995
7 'http://www.isi.edu/nsnam/ns/ucb-tutorial.html'
8 Jacek M. Zurada, 'Introduction to Artificial Neural Systems', West Publishing Company, 1992
9 M. Mahdavie and S.Floyed. TCP-friendly unicast rate-based flow control Note sent to end2end-internet mailing list, Jan 1997
10 W. S. McCulloch and W. H. Pitts, 'A Logical calculus for the ideas immanent in nervous activity', Bulletin of Mathematical Biophysics, vol.5, pp. 115-133, 1943   DOI
11 'http://www.isi.edu/nsnam/ns/ns-build.html' The Network Simulator, version 2
12 V. Paxson, End-To-End Internet packet dynamics. In Proceedings of SIGCOMM 97, 1997
13 A.S Tanenbaum, Computer Networks(third edition), Prentice Hall International, Inc., 1996
14 B. Widrow and M. A. Lehr, '30 years of adaptive neural networks Perceptron, Madaline, and backpropagation', Proceedings of the IEEE, vol. 78 no. 9 pp. 1415-1442, Sept. 1990   DOI   ScienceOn
15 V. Paxson, Automated packet trace analysis of TCP Implementations. IN Proceedings of SIGCOMM 97, 1997
16 Q.Zhand, G.Wang, W.Zhu, and Y.Zhang, 'Robust scalable video streaming over internet with network-adaptive congestion control and unequal loss protection, 'Technical Paper. Microsoft Research, Beijing, China, 2001
17 V. Jacobson. 'Congestion Avoidance and Control' SIGCOMM Symposium on Communications Architectures and Protocols, pages 214-329, 1988