Research On Some Problems In Internet Congestion Control Algorithms

The development of Internet has been encumbered with the congestion problem caused by the unbalance distribution of the network resources and the network flows since its naissance. The network congestion becomes more and more serious because of the increasingly expansion of Internet scale and the rapid growth of applied categories. The success of Internet has already proven that TCP congestion control mechanism based on source nodes is effective in the prevention of congestion collapse, while it also faces many new crises. Therefore, the network itself also has to be participated in congestion control. Currently, the combination of TCP congestion control mechanism based on source nodes and congestion avoidance mechanism based on network nodes has becomes a main approach to resolve the Internet congestion control problem. There has come into being a new investigation for some cross-subjects of computer network, communication, and automatic control and so on.Internet congestion control system can be seen as a nonlinear dynamic feedback system with communication delays. This paper emphasized on designs of active queue management (AQM) algorithms in network nodes for Internet congestion control, and stability analysis of network congestion control system. The main research results are as follows:(1) A robust nonlinear AQM algorithm is proposed to resolve the time-delays and parameters time-varying influence on the performance in middle or small-scale network, which is based on a first-order time-delays system with parametric interval uncertainty derived from fluid-flow model. The region of the nonlinear controller parameters making the closed-loop system stable is ascertained and the optimal parameters of the controller is obtained using genetic algorithm with the improved integrated time absolute error (ITAE). The edge theorem extended to time-delays systems is used to design a robust nonlinear AQM algorithm. Simulation results show the controller can achieve favorable performances and is robust against parametric interval uncertainties.(2) A predictive proportional integral (PPI) algorithm for active queue management is proposed to cope with the large delays in large-scale network. In PPI algorithm, Smith predictor is utilized to deal with large delays and Dahlin principle is employed to design controller to reduce the numbers and interactions of the tuning parameters. At the same time, a classical control method is introduced to analyze the stability of the system and the transients as well as steady-state behaviors of bottleneck queue with link capacity disturbances. The simulation results show PPI algorithm's advantages through comparisons among random early detection (RED) and proportional integral (PI) algorithms.(3) An adaptive mechanism for PPI algorithm is designed to deal with large-scale network parameters immense varying problems. The control parameters are automatically tuned according to on-line estimation of link capacity and traffic load, which makes PPI perform well for a wide-range of network conditions. The local stability of the overall system and the setting principle of adaptive parameters are analyzed using the method of linearization. The simulation results show the APPI algorithm is very robust against network parameters immense variance.