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


Vol. 30,  No. 2, pp. 44-52, Feb.  2005


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  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.

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  Cite this article

[IEEE Style]

Y. Kim, B. Kwon, K. T. Chong, "A Real-Time Multimedia Data Transmission Rate Control Using Neural Network Prediction Model," The Journal of Korean Institute of Communications and Information Sciences, vol. 30, no. 2, pp. 44-52, 2005. DOI: .

[ACM Style]

Yong-Seok Kim, Bang-Hyun Kwon, and Kil To Chong. 2005. A Real-Time Multimedia Data Transmission Rate Control Using Neural Network Prediction Model. The Journal of Korean Institute of Communications and Information Sciences, 30, 2, (2005), 44-52. DOI: .

[KICS Style]

Yong-Seok Kim, Bang-Hyun Kwon, Kil To Chong, "A Real-Time Multimedia Data Transmission Rate Control Using Neural Network Prediction Model," The Journal of Korean Institute of Communications and Information Sciences, vol. 30, no. 2, pp. 44-52, 2. 2005.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880