Modeling QoS Parameters of VoIP Traffic with Multifractal and Markov Models

  • Homero Toral-Cruz
  • Al-Sakib Khan Pathan
  • Julio C. Ramírez-Pacheco
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7017)

Abstract

In this paper, we analyze the jitter and packet loss behavior of voice over Internet protocol (VoIP) traffic by means of networks measurements and simulations results. As result of these analyses, we provide a detailed characterization and accurate modeling of these Quality of Service (QoS) parameters. Our studies have revealed that VoIP jitter can be modeled by self-similar and multifractal models. We present a methodology for simulating packet loss. Besides, we found relationships between Hurst parameter (H) with packet loss rate (PLR).

Keywords

VoIP PLR Jitter H Parameter Markov Chains Multifractality 

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References

  1. 1.
    Markopouloua, A., Tobagib, F., Karam, M.: Loss and Delay Measurements of Internet Backbones. Computer Communications 29(10), 1590–1604 (2006)CrossRefGoogle Scholar
  2. 2.
    Karapantazis, S., Pavlidou, F.-N.: VoIP: A comprehensive survey on a promising technology. Computer Networks 53(12), 2050–2090 (2009)CrossRefGoogle Scholar
  3. 3.
    Salah, K.: On the deployment of VoIP in Ethernet networks: methodology and case study. Computer Communications 29(8), 1039–1054 (2006)CrossRefGoogle Scholar
  4. 4.
    Turunen, J., Loula, P., Lipping, T.: Assessment of objective voice quality over best-effort networks. Computer Communications 28(5), 582–588 (2005)CrossRefGoogle Scholar
  5. 5.
    Zhang, L., Zheng, L., Ngee, K.S.: Effect of delay and delay jitter on voice/video over IP. Computer Communications 25(9), 863–873 (2002)CrossRefGoogle Scholar
  6. 6.
    Park, K., Willinger, W.: Self-Similar Network Traffic and Performance Evaluation, ch. 1. John Wiley & Sons, Inc., Chichester (2000)CrossRefGoogle Scholar
  7. 7.
    Paxson, V., Floyd, S.: Wide area traffic: the failure of Poisson modeling. IEEE/ACM Transactions on Networking (TON) 3(3), 226–244 (1995)CrossRefGoogle Scholar
  8. 8.
    Veitch, D., Hohn, N., Abry, P.: Multifractality in TCP/IP traffic: the case against. Computer Networks 48(3), 293–313 (2005)CrossRefGoogle Scholar
  9. 9.
    Riedi, R., Véhel, J.: Multifractal properties of TCP traffic: A numerical study. Technical Report No. 3129, INRIA Rocquencourt, France (1997), www.dsp.rice.edu/~riedi
  10. 10.
    Gilbert, A., Willinger, W., Feldmann, A.: Scaling analysis of conservative cascades, with applications to network traffic. IEEE Trans. Info. Theo. 45(3), 971–992 (1999)MathSciNetCrossRefMATHGoogle Scholar
  11. 11.
    Yajnik, M., Moon, S., Kursoe, J., Towsley, D.: Measurement and modelling of the temporal dependence in packet loss. In: Proc. IEEE INFOCOM 1999, NY, pp. 345–352 (1999)Google Scholar
  12. 12.
    Tarnay, K., Adamis, G., Dulai, T.: Advanced Communication Protocol Technologies: Solutions, Methods, and Applications, ch. 17. IGI Global (2011)Google Scholar
  13. 13.
    Advanced Information CTS (Centro de Tecnología de Semiconductores) Property, Alliance FXO/FXS/E1 VoIP System, www.cts-design.com
  14. 14.
    Wireshark: A Network Protocol Analyzer, http://www.wireshark.org/
  15. 15.
    Toral, H.: QoS Parameters Modeling of Self-similar VoIP Traffic and an Improvement to the E Model. PhD. Thesis, Electrical Engineering, Telecommunication Section, CINVESTAV, Guadalajara, Jalisco, Mexico (2010) Google Scholar
  16. 16.
    RFC 3550, RTP: A Transport Protocol for Real-Time Applications. Internet Engineering Task Force (2003), http://www.ietf.org/rfc/rfc3550.txt
  17. 17.
    Yee, J.R., Weldon Jr., E.J.: Evaluation of the Performance of Error-Correcting Codes on a Gilbert Channel. IEEE Trans. on Communications 43(8), 655–659 (1995)CrossRefMATHGoogle Scholar
  18. 18.
    Fitzek, F.H.P., Reisslein, M.: MPEG-4 and H. 263 video traces for network performance evaluation. IEEE Network 15(6), 40–54 (2001)CrossRefGoogle Scholar
  19. 19.
    Veitch, D., Abry, P.: A wavelet based joint estimator for the parameters of LRD. IEEE Transactions on Information Theory 45(3), 878–897 (1999)MathSciNetCrossRefMATHGoogle Scholar
  20. 20.
    Estrada, L., Torres, D., Toral, H.: Variance Error for Finite-length Self-similar Time Series. In: 7th International Conference on Computing, Communications and Control Technologies (CCCT 2009), Orlando, Florida, USA, pp. 193–198 (2009) Google Scholar
  21. 21.
    Raake, A.: Short- and Long-Term Packet Loss Behavior: Towards Speech Quality Prediction for Arbitrary Loss Distributions. IEEE Transactions on Audio, Speech, and Language Processing 14(6), 957–1968 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Homero Toral-Cruz
    • 1
    • 2
  • Al-Sakib Khan Pathan
    • 3
  • Julio C. Ramírez-Pacheco
    • 4
  1. 1.Dept. of Sciences and EngineeringUniversidad de Quintana RooMéxico
  2. 2.Dept. of PostgraduateInstituto Tecnológico Superior de Las ChoapasMéxico
  3. 3.Dept. of Computer ScienceInternational Islamic University MalaysiaMalaysia
  4. 4.Dept. of Basic Sciences and EngineeringUniversidad Del CaribeMéxico

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