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Analysis of quality-of-service metrics in IMS networks

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Abstract

A network constructed according to the IMS architecture consists of different modules that sequentially process signaling messages transferred during providing communication services. Delays that occur when processing signaling messages determine the quality of service for subscribers. International recommendations define the quality-of-service metrics, which include not only the mean, but also the 95% quantile. The paper proposes an approach to analyzing the quality-of-service characteristics. It is assumed that IMS-network nodes work as multi-server queues with general service time distribution.

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References

  1. Rosenberg, J. et al., SIP: Session Initiation Protocol RFC 3261, IETF, June 2002.

    Google Scholar 

  2. Calhoun, P. et al., Diameter Base Protocol RFC 3588, IETF, September 2003.

    Google Scholar 

  3. 3GPP, Network architecture, TS 23.002 (V12.4.0), March 2014.

    Google Scholar 

  4. 3GPP, Policy and charging control architecture, TS 23.203 (V12.4.0), March 2014.

    Google Scholar 

  5. ITU-T Recommendation Y.1531, 2007. SIP-based Call Processing Performance.

    Google Scholar 

  6. Malas, D. et al., Basic Telephony SIP End-to-End Performance Metrics RFC 6076, IETF, January 2011.

    Google Scholar 

  7. ITU-T Recommendation E.721, 1999. Network grade of service parameters and target values for circuitswitched services in the evolving ISDN.

  8. MGTS introduces IMS platform and accelerates launch of new services. http://mgtsru/company/ press/news/344479/#

  9. Erlang, A., The theory of probabilities and telephone conversations Nyt Tidsskrift for Matematik, 1909, vol. 20, pp. 33–39.

    Google Scholar 

  10. Yang, S. and Chen, W., SIP multicast-based mobile quality-of-service support over heterogeneous IP multimedia subsystems, Mobile Comput., IEEE Trans., 2008, vol. 7, no. 11.

    Google Scholar 

  11. Abaev, P., Razumchik, R., and Uglov, I., Statistical analysis of message delay in SIP proxy server J. Telecommun. Inf. Technol., 2014, no. 4.

  12. Poikselka, M. and Mayer, G., The IMS: IP Multimedia Concepts and Services John Wiley and Sons, Ltd., 2009, 3rd ed.

    Google Scholar 

  13. Ahson, A. and Ilyas, M., IP Multimedia Subsystem (IMS) Handbook, Boca Raton, FL: Taylor & Francis Group, 2009.

    Google Scholar 

  14. Cramer, H., Mathematical Methods of Statistics, Princeton: Princeton University Press, 1946.

    MATH  Google Scholar 

  15. Malakhov, A., Kumulyantnyi analiz sluchainykh negaussovykh protsessov i ikh preobrazovanie (Cumulant Analysis of Random Non-Gaussian Process and Their Transformation), Sovetskoe Radio: Moscow, 1975.

    Google Scholar 

  16. Burke, P.J., The dependence of sojourn times in tandem M/M/s queues Oper. Res., 1969, no. 17.

  17. Kiessler, P.C., Melamed, B., Yadin, M., and Foley, R.D., Analysis of a three node queueing network Queueing Syst., 1988, no. 3.

  18. Lee, A.M. and Longton, P.A., Queuing processes associated with airline passenger check-in J. Oper. Res. Soc., 1959, no. 10, pp. 56.

    Article  Google Scholar 

  19. Hokstad, P., Approximations for the M/G/m Queue Oper. Res. (INFORMS), 1978, vol. 26, no. 3, pp. 510–523.

    Article  MATH  Google Scholar 

  20. Kollerstrom, J., Heavy traffic theory for queues with several servers J. Appl. Probab. (Appl. Probab. Trust), 1974, vol. 11, no. 3, pp. 544–552.

    Article  MathSciNet  MATH  Google Scholar 

  21. Boxma, O. and Cohen, J., Approximations of the mean waiting time in an M/G/s queuing system Oper. Res. (INFORMS), 1979, vol. 27, no. 6, pp. 1115–1127.

    Article  MATH  Google Scholar 

  22. Bertsimas, D. and Nakazato, D., The distributional Little’s law and its applications Oper. Res., 1995, pp. 298–310.

    Google Scholar 

  23. Tijms, H.C., A First Course in Stochastic Models, West Sussex: A John Wiley and Sons, Ltd., 2003.

    Book  MATH  Google Scholar 

  24. Kleintrok, L., Teoriya massovogo obsluzhivaniya. Mashinostroenie (Queueing Theory. Mechanical Engineering), Moscow, 1979.

    Google Scholar 

  25. Hanbali, A. Al, Alvarez, E.M., and Heijden, M.C. van der, Approximations for the waiting-time distribution in an M/PH/c priority queue, OR Spectrum, 2015, vol. 37, no. 2, pp. 529–552.

    Article  MATH  Google Scholar 

  26. Cornish, E.A. and Fisher, R.A., Moments and cumulants in the specification of distributions Revue de l’Institut International de Statistique, 1937, no. 5, pp. 307–320.

    Article  MATH  Google Scholar 

  27. Kulikov, N., Analysis of QoS estimation methods in IMS-networks Telecommun. Transp., 2014, no. 10, pp. 96–99.

    Google Scholar 

Download references

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Authors and Affiliations

  1. R&D PROTEI, Bol’shoi Sampsonievskii 60A, St. Petersburg, 194044, Russia

    N. Kulikov

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  1. N. Kulikov
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Correspondence to N. Kulikov.

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Published in Russian in Avtomatika i Vychislitel’naya Tekhnika, 2016.

The article was translated by the authors.

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Kulikov, N. Analysis of quality-of-service metrics in IMS networks. Aut. Control Comp. Sci. 50, 37–45 (2016). https://doi.org/10.3103/S0146411616010077

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  • DOI: https://doi.org/10.3103/S0146411616010077

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