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TCP Westwood and Easy RED to Improve Fairness in High-Speed Networks

  • Luigi Alfredo Grieco
  • Saverio Mascolo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2334)

Abstract

TCP Westwood (TCPW) is a sender-side only modification of TCP Reno congestion control, which exploits end-to-end bandwidth estimation to properly set the values of slow-start threshold and congestion window after a congestion episode. This paper aims at showing via both mathematical modeling and extensive simulations that TCPW significantly improves fair sharing of high-speed networks capacity and that TCPW is friendly to TCP Reno. Moreover, we propose EASY RED, which is a simple Active Queue management (AQM) scheme that improves fair sharing of network capacity especially over high-speed networks. Simulation results show that TCP Westwood provides a remarkable Jain’s fairness index increment up to 200% with respect to TCP Reno and confirm that TCPW is friendly to TCP Reno. Finally, simulations show that Easy RED improves fairness of Reno connections more than RED, whereas the improvement in the case of Westwood connections is much smaller since Westwood already exhibits a fairer behavior by itself.

Keywords

Congestion Control Congestion Window Fairness Index Bottleneck Link Random Early Detection 
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.
    Jacobson, V.: Congestion Avoidance and Control. ACM Computer Communications Review, Vol. 18(4) (1988) 314–329CrossRefGoogle Scholar
  2. 2.
    Allman, M., Paxson, V., Stevens, W. R.: TCP congestion control. RFC 2581, April 1999Google Scholar
  3. 3.
    Mascolo, S., Casetti, C., Gerla, M., Sanadidi, M., Wang, R.: TCP Westwood: End-to-End Bandwidth Estimation for Efficient Transport over Wired and Wireless Networks. Proceedings of ACM Mobicom, Rome Italy (2001). To appear in ACM Journal on Wireless Networks (WINET), Special Issue on Wireless Networks with selected papers from MOBICOM2001Google Scholar
  4. 4.
    Clark, D.: The design philosophy of the DARPA Internet protocols. Proceedings of Sigcomm in ACM Computer Communication Review, Vol. 18(4) (1988) 106–114CrossRefGoogle Scholar
  5. 5.
    Floyd, S., Fall, K.: Promoting the use of end-to-end congestion control in the Internet. IEEE/ACM Transactions on Networking, Vol. 7(4) (1999) 458–72CrossRefGoogle Scholar
  6. 6.
    Mogul, J.C.: Observing TCP dynamics in real networks. Proceedings of Sigcomm in ACM Computer Communication Review, Vol. 22(4) (1992) 305–317CrossRefGoogle Scholar
  7. 7.
    ns-2 network simulator (ver 2). LBL, URL: http://www-mash.cs.berkeley.edu/ns
  8. 8.
    Jain, R.: The art of computer systems performance analysis. John Wiley and Sons, (1991)Google Scholar
  9. 9.
    Stevens, W.: TCP/IP illustrated, Addison Wesley, Reading, MA, (1994)zbMATHGoogle Scholar
  10. 10.
    Iannaccone, g., May, M, and Diot, C.: Aggregate Traffic Performance with Active Queue Management and Drop from Tail, Computer Communication Review, Vol. 31(3) (2001) 4–13CrossRefGoogle Scholar
  11. 11.
    Capone, A., Martignon, F.: Bandwidth Estimates in the TCP Congestion Control Scheme. Tyrrhenian IWDC 2001, Taormina Italy (2001)Google Scholar
  12. 12.
    Hoe, J., C., Improving the Start-up Behavior of a Congestion Control Scheme for TCP. Proceedings of ACM Sigcomm in ACM Computer Communication Review, Vol 26(4) (1996) 270–280CrossRefGoogle Scholar
  13. 13.
    Morris, R.: TCP behavior with Many Flows. IEEE International Conference on Network Protocols, Atlanta Georgia (1997) 205–211Google Scholar
  14. 14.
    Keshav, S.: A control-theoretic approach to flow control. Proceedings of Sigcomm in ACM Computer Communication Review, Vol. 21(4) (1991) 3–15CrossRefGoogle Scholar
  15. 15.
    Allman M., and Paxson, V.: On Estimating End-to-End Network Path Properties. Proceedings of Sigcomm in ACM Computer Communication Review, (1999) 263–274Google Scholar
  16. 16.
    Lai, K. and Baker, M.: Measuring Link Bandwidths Using a Deterministic Model of Packet Delay. Proceedings of Sigcomm in ACM Computer Communication Review, (2000) 283–294Google Scholar
  17. 17.
    Li, S.Q., and Hwang, C.: Link Capacity Allocation and Network Control by Filtered Input Rate in High speed Networks. IEEE/ACM Transactions on Networking, Vol. 3(1) (1995) 10–25CrossRefGoogle Scholar
  18. 18.
    Kelly, F.: Mathematical modeling of the Internet. Proceedings of the Fourth International Congress on Industrial and Applied Mathematics, (1999) 105–116Google Scholar
  19. 19.
    Floyd S., and Jacobson, V.: Random Early Detection gateways for congestion avoidance. IEEE/ACM Transactions on Networking, Vol 1(4) (1997)Google Scholar
  20. 20.
    Hollot, C.V., Misra, V., Towsley, D., and Gong, W.: A control Theoretic Analysis of RED. Proceedings of Infocom (2001)Google Scholar
  21. 21.
    May, M., Bolot, J., Diot, C., Lyles, B.: Reasons not to deploy RED. Seventh International Workshop on Quality of Service IWQoS (1999)Google Scholar
  22. 22.
    Hollot, C.V., Misra, V., Towsley, D., and Gong, W.: On Designing Improved Controllers for AQM Routers Supporting TCP Flows. Proceedings of Infocom (2001)Google Scholar
  23. 23.
    Floyd, S.: RED: Discussions of Setting Parameters, (1997). At http://www.aciri.org/floyd/
  24. 24.
    Floyd, S.: Recommendation on using the “gentle” variant of RED, (2000). At http://www.aciri.org/floyd/
  25. 25.
    Padhye, J., Firoiu, V., Towsley, D., Kurose, J.: Modeling TCP Throughput: A Simple Model and its Empirical Validation. Proceedings of Sigcomm in ACM Computer Communication Review, Vol 28(4) (1998) 303–314CrossRefGoogle Scholar
  26. 26.
    Floyd, S., Handley, M., Padhye, J., and Widmer, J.: Equation-Based Congestion Control for Unicast Applications. Proceedings of Sigcomm in ACM Computer Communication Review, Vol. 18 (2000) 43–56CrossRefGoogle Scholar
  27. 27.
    Feng, W., Kandlur, D., Saha, D., Shin, K.G.: A Self-Configuring RED Gateway. Proceedings of Infocom (1999)Google Scholar
  28. 28.
    Lin, D., and Morris, R.: Dynamics of Random Early Detection. Proceedings of Sigcomm in ACM Computer Communication Review, Vol. 27(4) (1997) 127–137CrossRefGoogle Scholar
  29. 29.
    Ott, T.J., Lakshman, T.V., Wong, L.: SRED: Stabilized RED. Proceedings of Infocom (1999)Google Scholar
  30. 30.
    Anjum, F.M., and Tassiulas, L.: Balanced RED: an algorithm to achieve fairness in the Internet. Proceedings of Infocom (1999)Google Scholar
  31. 31.
    Aweya, J., Ouellette, M., Montuno, D.Y.: A control theoretic approach to active queue management. Computer Networks, Vol. 36 (2001) 203–235CrossRefzbMATHGoogle Scholar
  32. 32.
    Floyd, S., Gummadi, R., Shenker, S.: Adaptive RED, An algorithm for Increasing the Robustness of RED’s Active Queue Management. Submitted for publication. Available at http://www.aciri.org/floyd/

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Luigi Alfredo Grieco
    • 1
  • Saverio Mascolo
    • 2
  1. 1.Dipartimento d’Ingegneria dell’InnovazioneUniversità di LecceItaly
  2. 2.Dipartimento di Elettrotecnica ed ElettronicaPolitecnico di BariItaly

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