Advertisement

Stabilization of Max-Min Fair Networks without Per-flow State

  • Jorge A. Cobb
  • Mohamed G. Gouda
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5340)

Abstract

Let a flow be a sequence of packets sent from a source computer to a destination computer. Routers at the core of the Internet do not maintain any information about the flows that traverse them. This has allowed for great speeds at the routers, at the expense of providing only best-effort service. In this paper, we consider the problem of fairly allocating bandwidth to each flow. We assume some flows request a constant amount of bandwidth from the network. The bandwidth that remains is distributed fairly among the rest of the flows. The fairness sought after is max-min fairness, which assigns to each flow the largest possible bandwidth that avoids affecting other flows. The distinguishing factor to other approaches is that routers only maintain a constant amount of state, which is consistent with trends in the Internet (such as the proposed Differentiated Services Internet architecture). In addition, due to the need for high fault-tolerance in the Internet, we ensure our protocol is self-stabilizing, that is, it tolerates a wide variety of transient faults.

Keywords

Stabilization max-min fairness quality of service computer networks 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Heinanen, J., Baker, F., Weiss, W., Wroclawski, J.: Assured forwarding phb group. Internet RFC 2597Google Scholar
  2. 2.
    Jacobson, V., Nichols, K., Poduri, K.: An expedited forwarding phb. Internet RFC 2598Google Scholar
  3. 3.
    Braden, R., Clark, D., Shenker, S.: Integrated services in the internet architecture. Internet RFC 1633Google Scholar
  4. 4.
    Wroclawski, J.: Specification of controlled-load network element service, Internet RFC 2211 (1997)Google Scholar
  5. 5.
    Boudec, J.-Y.L.: Rate adaptation, congestion control and fairness (2008), http://ica1www.epfl.ch/PS_files/LEB3132.pdf
  6. 6.
    Abraham, S., Kumar, A.: A stochastic approximation approach for max-min fair adaptive rate control of abr sessions with mcrs. In: Proceedings of IEEE INFOCOM, New York, NY (March 1999)Google Scholar
  7. 7.
    Charny, A.: An algorithm for rate allocation in a packet switching network with feedback, M.S. thesis, Massachusetts Institute of Technology (May 1994)Google Scholar
  8. 8.
    Hou, Y.T., Tzeng, H.H.Y., Panwar, S.S.: A generalized max-min rate allocation policy and its distributed implementation using the abr flow control mechanism. In: Proceedings of IEEE Infocom, San Francisco, CA (March 1998)Google Scholar
  9. 9.
    Ros, J., Tsai, W.K.: A general theory of constrained max-min rate allocation for multicast networks. In: IEEE International Conference on Networks, Singapore (2000)Google Scholar
  10. 10.
    Sarkar, S., Ren, T., Tassiulas, L.: Achieving fairness in multicasting with almost stateless rate control. In: Proceedings of the conference on Scalability and Traffic Control in IP Networks, SPIE, ITcom (2002)Google Scholar
  11. 11.
    Kim, Y., Tsai, W.K., Iyer, M., Ros, J.: Minimum rate guarantee without per-flow information. In: ICNP 1999: Proceedings of the Seventh Annual International Conference on Network Protocols, Washington, DC, USA, p. 155. IEEE Computer Society, Los Alamitos (1999)Google Scholar
  12. 12.
    Arora, A., Gouda, M.: Closure and convergence: A foundation of fault-tolerant computing. IEEE Transactions on Software Engineering 19(11), 1015–1027 (1993)CrossRefGoogle Scholar
  13. 13.
    Dolev, S., Herman, T.: Superstabilizing protocols for dynamic distributed systems. Chicago Journal of Theoretical Computer Science 1997(4) (1997)Google Scholar
  14. 14.
    Dijkstra, E.W.: Self-stabilizing systems in spite of distributed control. Commun. ACM 17(11), 643–644 (1974)CrossRefzbMATHGoogle Scholar
  15. 15.
    Stoica, I., Zhang, H.: Providing guaranteed services without per-flow management. In: Proc. of the ACM SIGCOMM Conference (1999)Google Scholar
  16. 16.
    Zhang, Z., Duan, Z., Gao, L., Hou, Y.T.: Decoupling QoS control from core routers: A novel bandwidth architecture for scalable support for guaranteed services. In: Proc. ACM SIGCOMM Conference (2000)Google Scholar
  17. 17.
    Kaur, J., Vin, H.M.: Core-stateless guaranteed rate scheduling algorithms. In: Proc. of the IEEE INFOCOM Conf. (2001)Google Scholar
  18. 18.
    Kaur, J., Vin, H.M.: Core stateless guaranteed throughput networks. In: Proc. of the IEEE INFOCOM Conf. (2003)Google Scholar
  19. 19.
    Callon, R., Doolan, P., Feldman, N., Fredette, A., Swallow, G., Viswanathan, A.: A framework for multiprotocol label switching, Internet draft draft-ietf-mpls-framework-02.txt (1997)Google Scholar
  20. 20.
    Cobb, J.: Preserving quality of service without per-flow state. In: Proc. IEEE International Conference on Network Protocols (ICNP) (November 2001)Google Scholar
  21. 21.
    Cobb, J.: Scalable quality of service across multiple domains. Computer Communications 28(18), 1997–2008 (2005)CrossRefGoogle Scholar
  22. 22.
    Cobb, J.A., Gouda, M.G.: Stabilization of max-min fair networks without per-flow state, Department of Computer Science Technical Report, The University of Texas at Dallas (September 2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Jorge A. Cobb
    • 1
  • Mohamed G. Gouda
    • 2
  1. 1.Department of Computer ScienceThe University of Texas at DallasUSA
  2. 2.Department of Computer ScienceThe University of Texas at AustinUSA

Personalised recommendations