A nonlinear rate control method for network congestion control

Yanping Xiang, Jianqiang Yi, Dongbin Zhao

Abstract: Traditional congestion control algorithms exhibit low convergence rate to equilibrium when the network capacity is very large. In this paper, we present a new algorithm called Quick Kelly Control (QKC) to accelerate the convergence rate. The link utilization ratio functions are used as feedback signal and a novel nonlinear update law is constructed. The stability of this new algorithm is partly proved without considering delay. We also compare this algorithm with two classic algorithms and give simulation results. It is shown that QKC has powerful bandwidth scalability and offers fast convergence rate without sacrificing proportional fairness.