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Outline

Analysis of on-off patterns in VoIP and their effect on voice traffic aggregation Wenyu Jiang, Henning Schulzrinne Department of Computer Science Columbia University Computer Communications and Networks, 2000. Proceedings. Ninth International Conference on.

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Outline

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  1. Analysis of on-off patterns in VoIP and their effect on voice traffic aggregationWenyu Jiang, Henning SchulzrinneDepartment of Computer Science Columbia UniversityComputer Communications and Networks, 2000. Proceedings. Ninth International Conference on Estimation of Token Bucket Parameters of VoIP TrafficR. Bruno, R.G.Garroppo and S.GiordanoDepartment of Information Engineering University of Pisa High Performance Switching and routing, 2000. ATM 2000 Proceedings of the IEEE Conference on , 2000

  2. Outline • Introduction • Experiment Setup • Comparisons with Traditional Silence Detectors • Token bucket simulations and results • Conclusions

  3. Introduction • Human speech consists of talk-spurts and silence gaps, also known as on-off patterns. • Allows higher bandwidth utilization through multiplexing. • Allows per-spurt play out delay adjustment. • Enable echo suppression based on silence detector output.

  4. Introduction (cont’d) energy Max (-20db) Min (-45db) time Pre-spurt hangover time Post-spurt hangover time

  5. Experiment Setup Mediatrix gateway 3COM Ethernet Phone 3COM Ethernet Phone

  6. Comparisons with Traditional Silence Detectors • Example spurt/gap distributions • NeVoT SD spurt and gap CDF using different parameters • Spurt/gap distribution after averaging over many conversations

  7. Example spurt/gap distributions

  8. Example spurt/gap distributions

  9. Example spurt/gap distributions

  10. NeVot SD spurt and gap CDF using different thresholds

  11. NeVot SD spurt and gap CDF using different thresholds

  12. NeVot SD spurt and gap CDF using different thresholds

  13. Spurt/gap distribution after averaging over many conversations

  14. Spurt/gap distribution after averaging over many conversations

  15. Spurt/gap distribution after averaging over many conversations

  16. Token bucket simulations and results

  17. Effect of spurt/gap distribution on multiplexing performance, G.729B

  18. Effect of spurt/gap distribution on multiplexing performance, G.729B

  19. Effect of spurt/gap distribution on multiplexing performance, G.729B

  20. Multiplexing performance for NeVoT SD with default parameters

  21. Multiplexing performance for NeVoT SD with default parameters

  22. Multiplexing performance for NeVoT SD with default parameters

  23. Equivalent Queuing Model

  24. Birth-and-death Markov Chain

  25. Simulation analysis Multiplexer token-bucket conditioner classifier

  26. Conclusions • Spurt/gap distributions are not exactly exponential, particularly for gaps. • The token bucket simulations result indicate that the exponential model generally gives a close estimate of the out-of-profile probability.

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