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Traffic Engineering with AIMD in MPLS Networks

  • Jianping Wang
  • Stephen Patek
  • Haiyong Wang
  • Jörg Liebeherr
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2334)

Abstract

We consider the problem of allocating bandwidth to competing flows in an MPLS network, subject to constraints on fairness, efficiency, and administrative complexity. The aggregate traffic between a source and a destination, called a flow, is mapped to label switched paths (LSPs) across the network. Each flow is assigned a preferred (‘primary’) LSP, but traffic may be sent to other (‘secondary’) LSPs. Within this context, we define objectives for traffic engineering, such as fairness, efficiency, and preferred flow assignment to the primary LSP of a flow (‘Primary Path First’, PPF). We propose a distributed, feedback-based multipath routing algorithm that attempts to apply additive-increase and multiplicative-decrease (AIMD) to implement our traffic engineering objectives. The new algorithm is referred to as multipath-AIMD. We use ns-2 simulations to illustrate the fairness criteria and PPF property of our multipath-AIMD scheme in an MPLS network.

Keywords

Congestion Control Fair Share Pool Resource Rate Allocation Primary Path 
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.

References

  1. 1.
    ns-2 network simulator. http://www.isi.edu/nsnam/ns/.
  2. 2.
    O. Aboul-Magd, L. Andersson, and P. Ashwood-Smith. Constraint-based LSP setup using LDP. http://www.ietf.org/internet-drafts/draft-ietf-mpls-cr-ldp-05.txt, February 2001.
  3. 3.
    I. F. Akyildiz, J. Liebeherr, and A. Tantawi. DQDB+/-: A fair and waste-free media access protocol for dual bus metropolitan networks. IEEE Transactions on Communications, 41(12):1805–1815, December 1993.CrossRefGoogle Scholar
  4. 4.
    D. O. Awduche, A. Chiu, A. Elwalid, I. Widjaja, and X. Xiao. Overview and principles of Internet traffic engineering. http://www.ietf.org/internet-drafts/draft-ietf-tewg-principles-02.txt, November 2001.
  5. 5.
    F. Bonomi and W. Fendick. The Rate-Based Flow Control Framework for the Available Bit Rate ATM Service. IEEE Network, 9(2):25–39, March/April 1995.CrossRefGoogle Scholar
  6. 6.
    D. Chiu and R. Jain. Analysis of the Increase and Decrease Algorithms for Congestion Avoidance in Computer Networks. Computer Networks and ISDN Systems, 17:1–14, 1989.CrossRefzbMATHGoogle Scholar
  7. 7.
    A. Elwalid, C. Jin, S. Low, and I. Widjaja. MATE: MPLS adaptive traffic engineering. In Proceedings of IEEE INFOCOM 2001, volume 3, pages 1300–1309, 2001.Google Scholar
  8. 8.
    D. O. Awduche et. al. RSVP-TE: Extensions to RSVP for LSP tunnels. http://www.ietf.org/internet-drafts/draft-ietf-mpls-rsvp-lsp-tunnel-09.txt, August 2001.
  9. 9.
    P. Hurley, J.-Y. Le Boudec, and P. Thiran. A note on the fairness of additive increase and multiplicative decrease. In Proceedings of ITC-16, Edinburgh, UK, June 1999.Google Scholar
  10. 10.
    V. Jacobson. Congestion avoidance and control. In Proceedings ofACMSigcomm’ 88, August, 1988, pages 314–329, 1988.Google Scholar
  11. 11.
    R. Jain. Congestion control and traffic management in ATM networks: Recent advances and a survey. Computer Networks and ISDN Systems, 28(13):1723–1738, October 1996.CrossRefGoogle Scholar
  12. 12.
    R. Jain and K. K. Ramakrishnan. Congestion avoidance in computer networks with a connectionless network layer: Concepts, goals and methodology. Proceedings of the Computer Networking Symposium; IEEE; Washington, DC, pages 134–143, 1988.Google Scholar
  13. 13.
    R. Jain, K. K. Ramakrishnan, and D.-M. Chiu. Congestion avoidance in computer networks with a connectionless network layer. December 1988. Digital Equipment Corporation, Technical Report DEC-TR-506.Google Scholar
  14. 14.
    F. P. Kelly. Charging and rate control for elastic traffic. European Transactions on Telecommunications, 8:33–37, 1997.CrossRefGoogle Scholar
  15. 15.
    F. P. Kelly, A. K. Maulloo, and D. K. H. Tan. Rate control for communication networks: Shadow prices, proportional fairness and stability. Journal of the Operational Research Society, 49:237–252, 1998.CrossRefzbMATHGoogle Scholar
  16. 16.
    S. Kunniyur and R. Srikant. End-to-end congestion control: Utility functions, random losses and ECN marks. In Proceedings of IEEE INFOCOM 2000, pages 1323–1332, March 2000.Google Scholar
  17. 17.
    K.-W. Lee, T.-E. Kim, and V. Bharghavan. A comparison of end-to-end congestion control algorithms: the case of AIMD and AIPD. In Proceedings of IEEE Globecom 2001, San Antonio, Texas, November 2001.Google Scholar
  18. 18.
    L. Massoulie and J. Roberts. Bandwidth sharing: Objectives and algorithms. In Proceedings IEEE INFOCOM 1999, New York, March 1999.Google Scholar
  19. 19.
    K. K. Ramakrishnan and R. Jain. A Binary Feedback Scheme for Congestion Avoidance in Computer Networks. ACM Transactions on Computer Systems, 8(2):158–181, 1990.CrossRefGoogle Scholar
  20. 20.
    E. Rosen, A. Viswanathan, and R. Callon. Multiprotocol label switching architecture. draft-ietf-mpls-arch-07.txt, ftp://ftp.isi.edu/in-notes/rfc3031.txt, January 2001.
  21. 21.
    M. Vojnovic, J.-Y. Le Boudec, and C. Boutremans. Global fairness of additive-increase and multiplicative-decrease with heterogeneous round-trip times. In Proceedings of IEEE INFOCOM 2000, volume 3, pages 1303–1312, 2000.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Jianping Wang
    • 1
  • Stephen Patek
    • 2
  • Haiyong Wang
    • 1
  • Jörg Liebeherr
    • 1
  1. 1.Department of Computer ScienceUniversity of VirginiaCharlottesvilleUSA
  2. 2.Department of Systems and Information EngineeringUniversity of VirginiaCharlottesvilleUSA

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