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Open-loop overload control algorithm for signalling traffic

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Abstract

In this paper a novel algorithm is proposed to solve the problem of overload control in telephony signalling services. The new algorithm can provide better performance than the traditional ones and is developed for a control architecture containing a token bucket followed by a buffer. The behavior of the control loop is influenced by three parameters: (i) the token rate of a token-bucket restrictor denoted by r; (ii) the relative deadline of response times; and (iii) the zero point of the response times.

Our concern is to optimize the control parameter r to maximize a utility function defined by two parameters: the relative deadline and the zero point of response times. The optimal control is sought by solving a constrained optimization problem in which we maximize the throughput under the constraint of tolerating a given response time.

In this way, one can fulfill a pre-defined QoS criterion, while achieving optimal system performance. This optimization entails the evaluation of the queue length dynamics based on a 2D Markovian model. From this calculation the p.d.f. of the queue length and the system time is expressed and the QoS parameters are analytically calculated as a function of the control parameters. The optimal rate parameter can then be found by traditional optimization methods.

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References

  1. Latouche, G., & Ramaswami, V. (1999). Introduction to matrix analytic methods in stochastic modeling. ASA-SIAM. ISBN 0-89871-425-7.

  2. Lu, C., Stankovic, J.A., Son, S.H., & Tao, G. (2002). Feedback control real-time scheduling: framework, modeling, and algorithms. Journal of Real-Time Systems, 23, 85–126.

    Article  Google Scholar 

  3. Stankovic, J.A., Ramamritham, K., & Towsley, D. (1991). Scheduling in real-time transaction systems. Technical Report: UM-CS-1991-046.

  4. Abdelzaher, T., & Sharma, V. (2003). A synthetic utilization bound for aperiodic tasks with resource requirements. In: Euromicro conference on real time systems, Porto, Portugal.

    Google Scholar 

  5. Kleinrock, L. (1975). Queueing systems, Vol. I: Theory. Wiley Interscience, New York. ISBN 978-0471491101.

    Google Scholar 

  6. Andersson, M., Kihl, M., & Robertsson, A. (2003). Modelling and design of admission control mechanisms for web servers using non-linear control theory. In: Proceedings of information technologies and communications, Orlando, Florida, USA.

    Google Scholar 

  7. Abdelzaher, T.F., Shin, K.G., & Bhatti, N. (2002). Performance guarantees for web server end-systems: a control theoretical approach. IEEE Transactions on Parallel and Distributed Systems, 13(1), 80–96.

    Article  Google Scholar 

  8. Fang, Y. (2001). Hyper-Erlang distribution model and its application in wireless mobile networks. Wireless Networks Archive, 7(3) (Special issue: Design and modeling in mobile and wireless systems).

  9. Thümmler, A., Buchholz, P., & Telek, M. (2006). A novel approach for phase-type fitting with the em algorithm. IEEE Transactions on Dependable and Secure Computing, 3(3), 245–258.

    Article  Google Scholar 

  10. Kasera, S., Pinheiro, J., Loader, C., LaPorta, T., Karaul, M., & Robust, A.H., (2005). Multiclass signaling overload control. In: Network Protocols, ICMP 13th IEEE international conference.

    Google Scholar 

  11. Robertsson, A., Wittenmark, B., & Kihl, M. (2004). Analysis and design of admission control in web-server systems. In: 43rd IEEE conference on decision and control, vol. 1, pp. 531–536.

    Google Scholar 

  12. Lin, H., Ghosh, P., & Das, P. (2006). Wireless networks revenue optimization overload control with priority services. Journal of Communications, 1(4).

  13. Williams, P.M., & Whitehead, M.J. (2002). Realising effective intelligent network overload controls. BT Technology Journal, 20(3), 55–75.

    Article  Google Scholar 

  14. Bobbio, A., Horváth, A., & Telek, M. (2005). Matching three moments with minimal acyclic phase type distributions. Stochastic Models, 21(2–3), 303–326.

    Article  Google Scholar 

  15. Rosenberg, J. (2008). Requirements for management of overload in the session initiation protocol. Request for Comments 5390, IETF.

  16. Whitehead, M. (2005). GOCAP—one standardised overload control for next generation networks. BT Technology Journal, 23(1), 147–153.

    Article  Google Scholar 

  17. Seres, G., Szlávik, A., Zátonyi, J., & Bíró, J. (2003). Towards efficient decision rules for admission control based on the many sources asymptotics. Performance Evaluation 53(3–4), 209–223.

    Article  Google Scholar 

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Authors and Affiliations

  1. Budapest University of Technology and Economics, 1112 Rákó utca 51/7, Budapest, Hungary

    Dániel Krupp

  2. BME Híradástechnikai Tanszék, Budapest University of Technology and Economics, Post Box 91, 1521, Budapest, Hungary

    János Levendovszky

Authors
  1. Dániel Krupp
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  2. János Levendovszky
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Correspondence to Dániel Krupp.

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Krupp, D., Levendovszky, J. Open-loop overload control algorithm for signalling traffic. Telecommun Syst 52, 387–396 (2013). https://doi.org/10.1007/s11235-011-9445-0

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  • DOI: https://doi.org/10.1007/s11235-011-9445-0

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