Exponential Convergence Flow Control Model for Congestion Control
Weirong Liu, Jianqiang Yi, Dongbin Zhao, John Ting-Yung Wen · 2006
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 them 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. In this paper, we present a novel flow control model based on Kelly model in which link price can be negative to improve the convergence rate. Further, The proposed model uses two bits of ECN field in IP header to feed back price instead of introducing new packet header data. By this approach, we can implement flow control scheme achieving exponential convergence in traditional TCP/IP datagram format. NS2 simulation results show that our model can keep the advantages of other flow mechanisms, such as fairness and asymptotic stability with more rapid convergence rate.