Exponential Convergence Flow Control Model for Congestion Control

  • Weirong Liu
  • Jianqiang Yi
  • Dongbin Zhao
  • John T. Wen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4113)


Recently, many new flow control mechanisms derived from classic Kelly model are proposed to solve network congestion problem. They perform well in stability, fairness or robustness. However, most of their convergence rates are linear since in classic Kelly model, link price is only positive. In addition, some need to introduce extra packet header to get price information. This paper presents a novel flow control model based on Kelly model in which the link price can be negative to improve the convergence rate. Further, The proposed model uses two bits of ECN field to feed back price instead of introducing new packet header data. Thus it can implement flow control scheme achieving exponential convergence in traditional TCP/IP datagram format. NS2 simulation results show that our model can keep fairness and asymptotic stability with more rapid convergence rate.


Congestion Control Packet Header Bottleneck Link Active Queue Management Negative Price 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Weirong Liu
    • 1
  • Jianqiang Yi
    • 1
  • Dongbin Zhao
    • 1
  • John T. Wen
    • 2
  1. 1.Laboratory of Complex Systems & Intelligence Science, Institute of AutomationChinese Academy of SciencesBeijingChina
  2. 2.Department of Electrical, Computer, and SystemsRensselaer Polytechnic InstituteUSA

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