On Achieving Proportional Loss Differentiation Using Dynamic-MQDDP with Differential Drop Probability

  • Kyungrae Cho
  • Sangtae Bae
  • Jahwan Koo
  • Jinwook Chung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4557)


More Recently, researchers have explored to provide a queue management scheme with differentiated loss guarantees for the future Internet. Various types of real time and non-real time traffic with varying requirements are transmitted over the Internet. The sides of a packet drop rate, an each class to differential drop probability on achieving a low delay and high traffic intensity. Improved a queue management scheme to be enhanced to offer a drop probability is desired necessarily. This paper considers multiple random early detection with differential drop probability which is a slightly modified version of the MQDDP model, to get the performance of the best suited, we analyzes its main control parameters (max th , min th , max p ) for achieving the proportional loss differentiation (PLD) model, and gives their setting guidance from the analytic approach. we propose Dynamic-multiple queue management scheme based on differential drop probability, called Dynamic-MQDDP, is proposed to overcome MQDDP’s shortcoming as well as supports static max p parameter setting values for relative and each class proportional loss differentiation. MQDDP is static according to the situation of the network traffic, Network environment is very dynamic situation. Therefore max p parameter values needs to modify too to the constantly and dynamic. The verification of the guidance is shown with figuring out loss probability using a proposed algorithm under dynamic offered load and is also selection problem of optimal values of parameters for high traffic intensity and show that Dynamic-MQDDP has the better performance in terms of packet drop rate. We also demonstrated using an ns-2 network simulation.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Boland, T., May, M., Bolot, J.C.: Analytic evaluation of RED performance. In: Proc. IEEE INFOCOM, Tel Aviv, Israel, pp. 1415–1424 (March 2000)Google Scholar
  2. 2.
    Aweya, J., Ouellette, M., Montuno, D.Y.: Proportional loss rate differentiation in a FIFO queue, Computer Communications, pp. 1851–1867 (2004)Google Scholar
  3. 3.
    Dovrolis, C., Ramanthan, P.: A case for relative differentiated services and the proportional differentiation model. IEEE Network 13(5), 26–34 (1999)CrossRefGoogle Scholar
  4. 4.
    Braden, B. et al.: Recommendation on queue management and congestion avoidance in the Internet, IETF RFC 2309 (April 1998)Google Scholar
  5. 5.
    Dovrolis, C., Ramanathan, P.: Proportional differentiated services, part II: loss rate differentiation and packet dropping. In: Proc. of IWQoS, pp. 52–61 (2000)Google Scholar
  6. 6.
    Floyd, S.: RED: discussions of setting parameters (November 1997), available at
  7. 7.
    Floyd, S., Jacobson, V.: Random early detection gateways for TCP congestion avoidance. IEEE/ACM Trans. Networking 1(4), 397–413 (1993)CrossRefGoogle Scholar
  8. 8.
    Koo, J., Shakhov, V.V., Choo, H.: An Enhanced RED-based scheme for differentiated loss guarantees. In: Proc. of 9th Asia-Pacific Network Operations and Management Symposium (2006)Google Scholar
  9. 9.
    Liebeherr, J., Christin, N.: JoBS: joint buffer management and scheduling for differentiated services. In: Proc. of IWQoS, pp. 404–418 (2001)Google Scholar
  10. 10.
    Shakhov, V.V., Koo, J., Choo, H.: On modelling reliability in RED gateways. In: Schärfe, H., Hitzler, P., Øhrstrøm, P. (eds.) ICCS 2006. LNCS (LNAI), vol. 4068, pp. 948–951. Springer, Heidelberg (2006)Google Scholar
  11. 11.
    Li, J.-S., Lai, H.-C.: Providing proportional differentiated services using PLQ. In: Proc. of Globecom, pp. 2280–2284 (2001)Google Scholar
  12. 12.
    Zeng, J., Ansari, N.: An enhanced dropping scheme for proportional differentiated services. In: Proc. of ICC, pp. 1897–1901 (2003)Google Scholar
  13. 13.
    Li, J.-S., Lai, H.-C.: Providing proportional differentiated services using PLQ. In: Proc. of Globecom, pp. 2280–2284 (2001)Google Scholar
  14. 14.
    Floyd, S., Jacobson, V.: Random Early Detection for Congestion Avoidance, IEEE/ACM (August 1993)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Kyungrae Cho
    • 1
  • Sangtae Bae
    • 2
  • Jahwan Koo
    • 1
  • Jinwook Chung
    • 1
  1. 1.School of Information and Communication Engineering , SungKyunKwan University, Chunchun-dong 300, Jangan-gu, Suwon, Gyeonggi-do 440-746South Korea
  2. 2.Dongwon Industry Bldg., 275, Yangjae-dong, Seocho-gu, Seoul, 137-130Korea

Personalised recommendations