Telecommunication Systems

, Volume 43, Issue 3–4, pp 253–263 | Cite as

Toward statistical QoS guarantees in a differentiated services network

  • Shengquan Wang
  • Dong Xuan
  • Riccardo Bettati
  • Wei Zhao
Article

Abstract

In this paper, we propose and analyze a methodology for providing statistical guarantees within the diffserv model in a network, which uses static-priority schedulers. We extend the previous work on statistical delay analysis and develop a method that can be used to derive delay bounds without specific information on flow population. With this new method, we are able to successfully employ a utilization-based admission control approach for flow admission. This approach does not require explicit delay computation at admission time and hence is scalable to large systems. We systematically analyze the performance of our approaches in terms of system utilization. As expected, our experimental data show that statistical services can achieve much higher utilization than deterministic services.

Keywords

Differentiated services Statistical service Real-time application Static-priority scheduling Utilization-based admission control 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Agrawal, G., Chen, B., Zhao, W., & Davari, S. (1992). Guaranteeing synchronous message deadlines with the timed token protocol. In Proceedings of IEEE ICDCS, June 1992. Google Scholar
  2. 2.
    Ayyorgun, S., & Cruz, R. (2004). A service-curve model with loss and a multiplexing problem. In Proceedings of IEEE ICDCS, 2004. Google Scholar
  3. 3.
    Blake, S., Black, D., Carlson, M., Davies, E., Wang, Z., & Weiss, W. (1998). An architecture for differentiated service. RFC 2474. Google Scholar
  4. 4.
    Braden, R., Clark, D., & Shenker, S. (1994). Integrated services in the Internet architecture: an overview. Internet RFC 1633. Google Scholar
  5. 5.
    Chang, C. (1994). Stability, queue length, and delay of deterministic and stochastic queueing networks. IEEE Transactions on Automatic Control, 39(5), 913. CrossRefGoogle Scholar
  6. 6.
    Choi, B., & Bettati, R. (2001). Endpoint admission control: network based approach. In Proceedings of IEEE ICDCS, April 2001. Google Scholar
  7. 7.
    Ciucu, F., Burchard, A., & Liebeherr, J. (2005). A network service curve approach for the stochastic analysis of networks. In Proceedings of ACM SIGMETRICS, 2005. Google Scholar
  8. 8.
    Cruz, R. (1991). A calculus for network delay, Part I & II. IEEE Transactions on Information Theory, 37(1), 114–141. CrossRefGoogle Scholar
  9. 9.
    Dailianas, A., & Bovopoulis, A. (1994). Real-time admission control algorithms with delay and loss guarantees in ATM networks. In Proceedings of IEEE INFOCOM, June 1994. Google Scholar
  10. 10.
    Figueira, N., & Pasquale, J. (1995). An upper bound on delay for the virtualclock service discipline. IEEE/ACM Transactions on Networking, 3(4), 399. CrossRefGoogle Scholar
  11. 11.
    Firoiu, V., Kurose, J., & Towsley, D. (1997). Efficient admission control for EDF schedulers. In Proceedings of IEEE INFOCOM, April 1997. Google Scholar
  12. 12.
    Georgiadis, L., Guérin, R., Peris, V., & Sivarajan, K. N. (1996). Efficient network QoS provisioning based on per node traffic shaping. IEEE/ACM Transactions on Networking, 4(4), 482. CrossRefGoogle Scholar
  13. 13.
    Jiang, Y. (2006). A basic stochastic network calculus. In Proceedings of ACM Sigcomm, 2006. Google Scholar
  14. 14.
    Knightly, E. (1996). H-BIND: A new approach to providing statistical performance guarantees to VBR traffic. In Proceedings of IEEE INFOCOM, March 1996. Google Scholar
  15. 15.
    Knightly, E. (1998). Enforceable quality of service guarantees for bursty traffic streams. In Proceedings of IEEE INFOCOM, March 1998. Google Scholar
  16. 16.
    Kurose, J. (1992) On computing per-session performance bounds in high-speed multi-hop computer networks. In Proceedings of ACM Sigmetrics, May 1992. Google Scholar
  17. 17.
    Liebeherr, J., Patek, S., & Yilmaz, E. (2000) Tradeoffs in designing networks with end-to-end statistical QoS guarantees. In Proceedings of IWQoS, June 2000. Google Scholar
  18. 18.
    Liebeherr, J., Patek, S. D., & Burchard, A. (2003). Statistical per-flow service bounds in a network with aggregate provisioning. In Proceedings of IEEE Infocom, 2003. Google Scholar
  19. 19.
    Liu, C., & Layland, J. (1973). Scheduling algorithms for multiprogramming in a hard real time environment. Journal of ACM, 20(1), 46. CrossRefGoogle Scholar
  20. 20.
    Mitra, D., & Morrison, J. (1994). Erlang capacity and uniform approximations for shared unbuffered resources. IEEE/ACM Transactions on Networking, 2(6), 558–570. CrossRefGoogle Scholar
  21. 21.
    Nicols, K., Jacobson, V., & Zhang, L. (1997). A Two-bit differentiated services architecture for the Internet, Internet-Draft. Google Scholar
  22. 22.
    Parekh, A.K., & Gallager, R.G. (1993). A generalized processor sharing approach to flow control in integrated services networks: the single-node case. IEEE/ACM Transactions on Networking, 2(6), 344–357. CrossRefGoogle Scholar
  23. 23.
    Stoica, I., & Zhang, H. (1999). Providing guaranteed services without per flow management. In Proceedings of ACM SIGCOMM, Sep. 1999. Google Scholar
  24. 24.
    Wang, S., Xuan, D., Bettati, R., & Zhao, W. (2001). Providing absolute differentiated services for real-time applications in static priority scheduling networks. In Proceedings of IEEE INFOCOM, April 2001. Google Scholar
  25. 25.
    Wang, S., Xuan, D., Bettati, R., & Zhao, W. (2001). Differentiated services with statistical real-time guarantees in static-priority scheduling networks. In Proceedings of IEEE RTSS, Dec. 2001. Google Scholar
  26. 26.
    Wang, S., Xuan, D., Bettati, R., & Zhao, W. A study of providing statistical QoS in a differentiated services network (Technical Report). Department of Computer Science, Texas A&M University. Google Scholar
  27. 27.
    Wrege, D., Knightly, E., Zhang, H., & Liebeherr, J. (1996). Deterministic delay bounds for VBR video in packet-switching networks: fundamental limits and practical tradeoffs. IEEE/ACM Transactions on Networking, 4(3), 352. CrossRefGoogle Scholar
  28. 28.
    Yates, D.J., Kurose, J.F., Towsley, D., & Hluchyj, M.G. (1994). On per-session end-to-end delay and the call admission problem for real time applications with QoS requirements. Journal of High Speed Networks, 3(4), 429–458. Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Shengquan Wang
    • 1
  • Dong Xuan
    • 2
  • Riccardo Bettati
    • 3
  • Wei Zhao
    • 4
  1. 1.The University of Michigan-DearbornDearbornUSA
  2. 2.The Ohio-State UniversityColumbusUSA
  3. 3.Texas A&M UniversityCollege StationUSA
  4. 4.The University of MacauMacau SARChina

Personalised recommendations