Evaluation of neural network architectures for MPEG-4 video traffic prediction

IEEE Transactions on Broadcasting

Volumn 52, Issue 2, 2006, Pages 184-192

  Abdennour, Adel ^a  

^a KING SAUD UNIVERSITY   (Saudi Arabia)

Author keywords

MPEG; Neural networks; Prediction; Video traffic

Indexed keywords

IMAGE COMPRESSION; MULTIMEDIA SYSTEMS; NEURAL NETWORKS; SIGNAL FILTERING AND PREDICTION; TELECOMMUNICATION TRAFFIC; TELEVISION BROADCASTING;

MPEG; PREDICTION; VIDEO SEQUENCES; VIDEO TRAFFIC;

VIDEO SIGNAL PROCESSING;

EID: 33744816481     PISSN: 00189316     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBC.2006.872994     Document Type: Article

References (19)

1. I. Habib, "Applications of neurocomputing in traffic management of ATM networks," Proc. IEEE, vol. 84, no. 10, pp. 1430-1440, 1996.
2. A. Adas, "Using adaptive linear prediction to support real-time VBR video under RCBR network service model." IEEE/ACM Trans. Networking, vol. 6, no. 5, pp. 635-644, 1998.
3. S. Yoo, "Efficient traffic prediction scheme for real time VBR MPEG video transmission over high speed networks." IEEE Trans. on Broadcasting, vol. 48, no. 1, pp. 10-18, 2002.
4. G. Chiruvolu, R. Sankar, and N. Ranaganathan, "VBR video traffic management using a predictor-based architecture," Computer Communication, vol. 23, no. 1, 2002.
5. W. Xu and A. Qureshi, "Adaptive linear prediction of MPEG video traffic." in 5th Int. Symp on Signal Processing and its Applications, vol. 1, 1999, pp. 67-70.
6. I. Habib, A. Tarraf, and T. Saadwi, "A neural network controller for congestion control in ATM multiplexer," Computer Networks, vol. 29, no. 3, pp. 325-334, 1997.
7. _, "A novel neural network controller using reinforcement learning method," IEEE J. Selected. Areas. Commun, vol. 12, no. 6, pp. 998-1007, 1994.
8. S. Mohamed, G. Rubino, H. Afifi, and F. Cervantes, "Real-time video quality assessment in packet networks: A neural network model," in Pmc. PDPTA'01, Las Vegas, NV, 2001, pp. 102-111.
9. C. Onyiagha, X. Kransiqi, and T. Clarkson, "Adaptive access control of ATM traffic using neural network," IEEE Globcom, vol. 1, pp. 201-205, 1996.
10. R. Drossu, T. Lakshman, Z. Obradovic, and C. Raghavendra, "Single and multiple frame video traffic prediction using neural network models," Computer Networks: Airhitecture and Applications, pp. 146-158, 1995.
11. P. Chang and J. Hu, "Optimal nonlinear adaptive prediction and modeling of MPEG video in ATM networks using pipelined recurrent neural networks," IEEE J. Selected. Areas. Commun, vol. 15, no. 6, pp. 1087-1100, 1997.
12. A. Doulamis, N. Doulamis, and S. Kollias, "An adaptable neural network model for recursive nonlinear traffic prediction and modeling of MPEG video sources," IEEE Trans. on Neural Nentworks, vol. 14, no. 1, pp. 150-166, 2003.
13. Y. Liang, "Real-time VBR video traffic prediction for dynamic band-width allocation," IEEE Trans. on Systems, Man, and Cybernetics, vol. 34, no. 1, pp. 32-47, 2004.
14. A. Bhattacharya, A. Parlos, and A. Atiya, "Prediction of MPEG-coded video source traffic using recurrent neural network," IEEE Trans. on Signal Processing, vol. 51, no. 8, pp. 2177-2190, 2003.
15. A. Khotanzad and N. Sadek, "Multi-scale high speed network traffic prediction using combination of neural networks," in International Joint Conf., on Neural Networks) IJCNN03), vol. 2, Portland, Oregon, 2003, pp. 1071-1075.
16. B. Qiu, S. Suthaharna, and H. Wu, "Neuro-fuzzy modeling and prediction of VBR MPEG video sources." ACM, vol. 5, no. 5, pp. 359-363, 1999.
17. MPEG-4 and H.263 Video Traces for Network Performance Evaluation, F. H. P. Fitzek. (2001, Nov/Dec). http:/www-tkn.ee.tu-berlin.de/research/trace/trace. htmlhttp://www-tkn.ee.tu-berlin.de/research/trace/trace.html. [Online]
18. D. Rumelhart, G. Hinton, and R. Williams, "Learning internal representations by error propagation," Parallel Distributed Processing: Exploring in the Microstructure of Cognition, vol. 1, pp. 318-362, 1986.
19. J. Hall and P. Mars, "Limitations of artificial neural networks for traffic prediction in broadband networks," IEE Proc. Communications, vol. 147, no. 2, pp. 114-118, 2000.