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Bounded Control of Multiple-Delay Systems with Applications to ATM Networks

  • Sophie Tarbouriech
  • Chaouki T. Abdallah
  • Marco Ariola
Conference paper
Part of the Lecture Notes in Computational Science and Engineering book series (LNCSE, volume 38)

Abstract

The transmission of multimedia traffic on the broadband integrated service digital networks (B-ISDN) has created the need for new transport technologies such as Asynchronous Transfer Mode (ATM). Briefly, because or the variability of the multimedia traffic, ATM networks seek to guarantee an end-to-end quality of service (QoS) by dividing the varying types of traffic (voice, data, etc.) into short, fixed-size cells (53 bytes each) whose transmission delay may be predicted and controlled. ATM is thus a Virtual Circuit (VC) technology which combines advantages of circuit-switching (all intermediate switches are alerted of the transmission requirements, and a connecting circuit is established) and packet-switching (many circuits can share the network resources). In order for the various VC’s to share network resources, flow and congestion control algorithms need to be designed and implemented. The congestion control problem is solved by regulating the input traffic rate. In addition, because of its inherent flexibility, ATM traffic may be served under one of the following service classes:

Keywords

Bound Control Asynchronous Transfer Mode Virtual Circuit Asynchronous Transfer Mode Network Asynchronous Transfer Mode Switch 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Abdallah CT, Ariola M, Byrne R (2000) Statistical-Learning Control of an ABR Explicit Rate Algorithm for ATM Switches. Proc. of the 39th IEEE Conference on Decision and Control. Sidney, Australia 53–54Google Scholar
  2. 2.
    Abdallah CT, Ariola M, Koltchinskii V (2001) Statistical-Learning Control of Multiple-Delay Systems with applications to ATM Networks. Kybernetica 37(3):355–365MathSciNetzbMATHGoogle Scholar
  3. 3.
    ATM Forum Traffic Management Working Group AF-TM-0056.000 (1996) ATM Forum Traffic Management Specification Version 4.0 Google Scholar
  4. 4.
    Benmohamed L, Wang YT (1998) A Control-Theoretic ABR Explicit Rate Algorithm for ATM Switches with Per-VC Queuing. In: Proceedings Infocom98, San Francisco, CA 183–191Google Scholar
  5. 5.
    Blanchini F, Lo Cigno R, Tempo R (1998) Control of ATM Networks: Fragility and Robustness Issues. Proc. of the American Control Conference, Philadelphia, PA, 2847–2851Google Scholar
  6. 6.
    Cavendish D, Mascolo S, Gerla M (1996) SP-EPRCA: an ATM rate Based Congestion Control Scheme Based on a Smith Predictor. UCLA CS Tech Report 960001, available at:ftp://ftp.cs.ucla.edu/tech-report/Google Scholar
  7. 7.
    Gahinet P, Nemirovski A, Laub AJ, Chilali M (1995) LMI Control Toolbox. The Mathworks Inc Natick MAGoogle Scholar
  8. 8.
    Hennet J-C, Tarbouriech S (1997) Stability and stabilization of delay differential systems. Automatica 33(3):347–354MathSciNetzbMATHCrossRefGoogle Scholar
  9. 9.
    Imer OC, Compans S, Başar T, Srikant R (2001) ABR Comrol in ATM Networks. IEEE Control Systems Magazine 21(1):38–56CrossRefGoogle Scholar
  10. 10.
    Imer OC, Compans S, Başar T, Srikant R (2001) Available Bit rate Congestion Control in ABR congestion. IEEE Control Systems Magazine 21(1):38–56CrossRefGoogle Scholar
  11. 11.
    Kohchinskii V, Abdallah CT, Ariola M, Dorato P, Panchenko D (2000) Improved Sample Complexity Estimates for Statistical Learning Control of Uncenain Systems. IEEE Trans. Autom. Control 45(12):2383–2388CrossRefGoogle Scholar
  12. 12.
    Mascolo S (2000) Smith’s Principle for Congestion Control in High-Speed Data Networks. IEEE Trans. Autom. Control 45(2):358–364MathSciNetzbMATHCrossRefGoogle Scholar
  13. 13.
    Saberi A, Lin Z, Teel AR (1996) Contol of linear systems with saturating actuators. IEEE Trans. Autom. Control 41(3):368–378MathSciNetzbMATHCrossRefGoogle Scholar
  14. 14.
    Seifert G (1976) Positively invariant closed-loop systems of delay differential equations. J. Differential Equations 22:292–304MathSciNetzbMATHCrossRefGoogle Scholar
  15. 15.
    Tarbouriech S, Garcia G (eds) (1997) Control of uneenain systems with bounded inputs. Lecture Notes in Control and Infonnation Sciences vo1.227, Springer-VerlagGoogle Scholar
  16. 16.
    Tarbouriech T, Gomes da Silva Jr. J-M (2000) Synthesis of controllers for continuous-time delay systems with saturating controls. IEEE Trans. Autom. Control 45(1): 105–110MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Sophie Tarbouriech
    • 1
  • Chaouki T. Abdallah
    • 2
  • Marco Ariola
    • 3
  1. 1.LAAS-CNRS, 7 Avenue du Colonel RocheToulouse cedex 4France
  2. 2.Electrical and Computer Engineering, University of New MexicoAlbuquerqueUSA
  3. 3.Dipartimento di Informatica e SistemisticaUniversità degli Studi di Napoli Federico IINapoliItaly

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