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Mathematical Problems in Engineering
Volume 2010, Article ID 984923, 9 pages
http://dx.doi.org/10.1155/2010/984923
Research Article

An Intelligent Packet Loss Control Heuristic for Connectionless Real-Time Voice Communication

1Department of Computing Science, University of Aberdeen, Aberdeen AB24 3FX, Scotland, UK
2Department of Computer Engineering, İstanbul Kültür University, 34156 İstanbul, Turkey
3Vocational School of Technical Sciences, İstanbul Kültür University, 34156 İstanbul, Turkey

Received 4 September 2009; Revised 1 April 2010; Accepted 21 April 2010

Academic Editor: Alexander P. Seyranian

Copyright © 2010 Murat Şensoy et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. W. R. Stevens, UNIX Network Programming: Networking APIs: Sockets and XTI, Prentice-Hall PTR, Upper Saddle River, NJ, USA, 1997.
  2. W. Jiang and H. Schulzrinne, “Modeling of packet loss and delay and their effect on real-time multimedia service quality,” in Proceedings of the Network and Operating System Support for Digital Audio and Video (NOSSDAV '00), pp. 1–10, 2000. View at Publisher · View at Google Scholar
  3. H. Sanneck and G. Carle, “A framework model for packet loss metrics based on loss runlengths,” in Proceedings of SPIE/ACM SIGMM Multimedia Computing and Networking Conference, pp. 177–187, 2000.
  4. H. L. Ferra, K. Lau, C. Leckie, and A. Tang, “Applying reinforcement learning to packet scheduling in routers,” in Proceedings of the 15th Conference on Innovative Applications of Artificial Intelligence, pp. 79–84, 2003. View at Publisher · View at Google Scholar
  5. D. H. Wolpert, K. Tumer, and J. Frank, “Using collective intelligence to route internet traffic,” in Proceedings of the Conference on Advances in Neural Information Processing Systems II, pp. 952–958, 1999.
  6. D. H. Wolpert, S. Kirshner, C. J. Merz, and K. Tumer, “Adaptivity in agent-based routing for data networks,” in Proceedings of the 4th International Conference on Autonomous Agents (AGENTS '00), pp. 396–403, 2000.
  7. J. A. Boyan and M. L. Littman, “Packet routing in dynamically changing networks: a reinforcement learning approach,” in Proceedings of the 24th Conference in Advances in Neural Information Processing Systems 6, pp. 671–678, Morgan Kaufmann, 1994.
  8. Y.-H. Chang, T. Ho, and L. P. Kaelbling, “Mobilized ad-hoc networks: a reinforcement learning approach,” in Proceedings of the International Conference on Autonomic Computing, pp. 240–247, 2004.
  9. G. Haßlinger and O. Hohlfeld, “The gilbert-elliott model for packet loss in real time services on the internet,” in Proceedings of the 14th GI/ITG Conference on Measurement, Modelling and Evaluation of Computer and Communication Systems (MMB '08), pp. 269–286, 2008.
  10. I. El Khayat, P. Geurts, and G. Leduc, “Enhancement of TCP over wired/wireless networks with packet loss classifiers inferred by supervised learning,” Wireless Networks, vol. 16, no. 2, pp. 273–290, 2010. View at Publisher · View at Google Scholar
  11. M. Mushkin and I. Bar-David, “Capacity and coding for the Gilbert-Elliot channels,” IEEE Transactions on Information Theory, vol. 35, no. 6, pp. 1277–1290, 1989. View at Publisher · View at Google Scholar
  12. M. Puterman, Markov Decision Processes, Wiley-Interscience, New York, NY, USA, 2005.
  13. D. H. Ballard, An Introduction to Natural Computation, MIT Press, Cambridge, Mass, USA, 1997.
  14. L. Kaelbling, M. Littman, and A. Moore, “Reinforcement learning: a survey,” Journal of Artificial Intelligence Research, vol. 4, pp. 237–285, 1996. View at Google Scholar
  15. B. S. Atal, “Linear predictive coding of speech,” Computer Speech Processing, pp. 81–124, 1985. View at Google Scholar