Performance of Active Queue Management Algorithms to Be Used in Intserv Under TCP and UDP Traffic

  • Ali Ucar
  • Sema Oktug
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3375)

Abstract

Active Queue Management techniques are recommended to overcome the performance limitations of TCP congestion control mechanisms over drop-tail networks. Flow Random Early Drop (FRED), GREEN, Stochastic Fair Blue (SFB), Stabilized RED (SRED) are some of the active queue management algorithms which are flow-based in nature. These algorithms can be used to implement Intserv. The main objective of this paper is to present a comparative analysis of the performance of the FRED, GREEN, SFB, and SRED algorithms using the NS-2 network simulator. In this work, the simulations are carried out for the comprehensive analysis and comparison of the algorithms. The algorithms are tested in terms of average queue size, fairness, utilization and packet loss rate by applying various number of flows under TCP, and TCP/UDP traffic.

Keywords

Packet Loss Rate Fairness Index Link Utilization Random Early Detection Congestion Avoidance 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Postel, J.: Transmission Control Protocol, RFC 793, IETF (1981)Google Scholar
  2. 2.
    Chiu, D., Jain, R.: Analysis of the Increase and Decrease Algorithms for Congestion Avoidance in Computer Networks. Comp. Networks and ISDN Sys. 17(1) (1989)Google Scholar
  3. 3.
    Floyd, S.: TCP and Explicit Congestion Notification. ACM Comp. Commun. Rev. 24(5) (1994)Google Scholar
  4. 4.
    Charny, A., Clark, D., Jain, R.: Congestion Control with Explicit Rate Indication. In: Proc. ICC (1995)Google Scholar
  5. 5.
    Floyd, S., Jacobson, V.: Traffic Phase Effects in Packet-switched Gateways. ACM Comp. Commun. Rev. 21(2) (1991)Google Scholar
  6. 6.
    Braden, B.: Recommendations on Queue Management and Congestion Avoidance in the Internet, RFC 2309, IETF (1998)Google Scholar
  7. 7.
    Ferguson, P., Huston, G.: Quality of Service: Delivering QoS on the Internet and in Corporate Networks. Wiley, Chichester (1998)Google Scholar
  8. 8.
    Jacobson, V.: Congestion Avoidance and Control. ACM Comp. Commun. Rev. 18(4) (1988)Google Scholar
  9. 9.
    Lin, D., Morris, R.: Dynamics of Random Early Detection. In: Proc. of ACM SIGCOMM (1997)Google Scholar
  10. 10.
    Floyd, S., Jacobson, V.: Random Early Detection Gateways for Congestion Avoidance. IEEE/ACM Trans. Net. 1(4) (1993)Google Scholar
  11. 11.
    Feng, W., Kapadia, A., Thulasidasan, S.: GREEN: Proactive Queue Management over a Best-Effort Network. In: Proceedings of IEEE Globecom, Taipei, Taiwan (2002)Google Scholar
  12. 12.
    Mathis, M., Semke, J., Mahdavi, J., Ott, T.: The Macroscopic Behavior of the TCP Congestion Avoidance Algorithm. Computer Communication Review 27(3) (1997)Google Scholar
  13. 13.
    Ott, T.J., Lakshman, T.V., Wong, L.H.: SRED: Stabilized RED. In: Proceedings of INFOCOM, vol. 3 (1999)Google Scholar
  14. 14.
    Feng, W., Kandlur, D., Saha, D., Shin, K.: Stochastic Fair Blue: A Queue Management Algorithm for Enforcing Fairness. In: Proc. of IEEE INFOCOM (2001)Google Scholar
  15. 15.
    NS, Network Simulator, http://www.isi.edu/nsnam/ns
  16. 16.
    Feng, W., Kandlur, D., Saha, D., Shin, K.: Blue: A New Class of Active Queue Management Algorithms. In: UM CSE-TR-387-99 (April 1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Ali Ucar
    • 1
  • Sema Oktug
    • 2
  1. 1.Renault MAIS, I.T.IstanbulTurkey
  2. 2.Department of Computer EngineeringIstanbul Technical UniversityMaslak, IstanbulTurkey

Personalised recommendations