Skip to main content
Log in

Bio-inspired auto-adaptive SIP overload controller

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

Abstract

In this article, a Session Initiation Protocol (SIP) overload control solution is proposed. It considers all the types of SIP requests. This is really what a SIP load is composed of, in an industrial environment. So far, the specialized literature considered INVITE messages only. So, we think that SIP servers are required to be dynamically adaptive to the diversity of the incoming load content. In the latter, the rate of a given SIP message type may be more or less than the other message types, depending on the services provided by the SIP server. Sometimes, it also depends on the time of the day. The auto-adaptation ability of the proposed overload control mechanism is designed after the immune system metaphor. The solution is validated through load tests and compared with a well known SIP overload control algorithm. Test load arrival patterns have been chosen to simulate three different service packages known in the SIP industry world as: Hosted Private Branch Exchange, Prepaid Calling Card Service, and Call-Shop Service.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Algorithm 1
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25

Similar content being viewed by others

References

  1. Abdelal, A., & &Matragi, W. (2010). Signal-based overload control for SIP servers. In Proceedings of the 7th IEEE consumer communications and networking conference, CCNC’10 (pp. 1–7).

    Google Scholar 

  2. Asterisk open source communications. Available from: http://www.asterisk.org/. Accessed: July 16th, 2011.

  3. Berek, C. (2005). Somatic hypermutation and b-cell receptor selection as regulators of the immune response. Transfusion Medicine and Hemotherapy, 32(6), 333–338.

    Article  Google Scholar 

  4. Hilt, V., & Widjaja, I. (2008). Controlling overload in networks of SIP servers. In Proceedings of the IEEE international conference on network protocols, ICNP’08 (pp. 83–93).

    Google Scholar 

  5. Homayouni, M., Jahanbakhsh, M., Azhari, V., & &Akbar, A. (2010). Overload control in SIP servers: evaluation and improvement. In Proceedings of the 17th IEEE international conference on telecommunications, ICT’10 (pp. 666–672).

    Google Scholar 

  6. Hwang, R., & Hoh, C. (2011). Cross-layer design of P2P file sharing over mobile ad hoc networks. Telecommunications Systems, 42(1–2), 47–61.

    Google Scholar 

  7. Marmol, F., & Perez, G. (2011). Providing trust in wireless sensor networks using a bio-inspired technique. Telecommunications Systems, 46(1–2), 163–180.

    Article  Google Scholar 

  8. Noel, E., & Johnson, C. (2009). Novel overload controls for SIP networks. In Proceedings of the 21st international teletraffic Congress (pp. 1–8).

    Google Scholar 

  9. Rosenberg, J. (2008). RFC 5390 requirements for management of overload in the session initiation protocol, December 2008.

  10. Rosenberg, J., Schulzrinne, H., Camarillo, G., Johnston, A., Peterson, J., Sparks, R., Handley, M., & Schooler, E. (2002). RFC 3261 SIP: Session initiation protocol, June 2002.

  11. Shen, C., Schulzrinne, H., & Nahum, E. (2008). Session initiation protocol (SIP) server overload control: design and evaluation. In Proceedings of the principles, systems and applications of IP telecommunications conference, IPTComm’08.

    Google Scholar 

  12. SIPp open source test tool. Available from: http://sipp.sourceforge.net/. Accessed: July 16th, 2011.

  13. Sun, J., Yu, H., & Zheng, W. (2008). Flow management with service differentiation for SIP application servers. In Proceedings of the 3rd ChinaGrid annual conference (pp. 272–277).

    Google Scholar 

  14. Tembine, H., Altman, E., El-Azouzi, R., & Hayel, Y. (2011). Bio-inspired delayed evolutionary game dynamics with networking applications. Telecommunications Systems, 47(1–2), 137–152.

    Article  Google Scholar 

  15. Yang, J., Huang, F., & Gou, S. (2009). An optimized algorithm for overload control of SIP signaling network. In Proceedings of the 5th international conference on wireless communications, networking and mobile computing, WiCOM’09 (pp. 1–4).

    Google Scholar 

Download references

Acknowledgements

Grateful acknowledgement is due to Imozaik Inc. for having provided some of the data used in this article.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zohair Chentouf.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chentouf, Z. Bio-inspired auto-adaptive SIP overload controller. Telecommun Syst 56, 481–492 (2014). https://doi.org/10.1007/s11235-013-9765-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11235-013-9765-3

Keywords

Navigation