Network congestion control mechanism is one of the key factors to maintain the stability and practicability of the Internet. The dissertation analyses the key factors of the network congestion problems and summarizes the significant research results. Further, concerning some insufficiency of these results, the dissertation proposes a series of extension to improve them. The main contents of the dissertation are listed as follows. Firstly, the phenomenon, cause, and general solution of the network congestion are introduced. And then, the current main network congestion mechanism, that is, TCP protocol is described. After that, the shortages of the TCP protocol are given and main improvements in recent research are discussed. Then background and main work of this dissertation are described. Secondly, it is pointed that taking packets losses as congestion signal is not proper in wireless network, so it is necessary to use explicit congestion notification to tell the sender the congestion occurring. The conventional ECN code is expanded to provide more state information about the network, and the AIMD mechanism of the TCP protocol is expanded to provide more smooth data flow. The simulation displays the proposed mechanisms can obtain more throughput and can keep low delay time. Thirdly, the fairness of the window-based congestion control mechanisms is analyzed and the unfairness problem depended on delay time of window-based mechanisms is pointed out. To obtain fine fairness, the Kelly fluid-based model is introduced which can realize global fairness. Fourthly, concerning the linear convergence speed of the primal algorithm in Kelly fairness model, a new fluid-based congestion control mechanism is proposed which can allow negative price in the link price updating. The introduced negative price can let the primal algorithm converge with exponential speed. Fifthly, to solve the overload problem of the primal algorithm in Kelly fairness model when the network is in steady state, a Genetic Algorithm-based Fuzzy Controller (GA-Fuzzy controller) is proposed which is used to adjust the additive increase factor of the primal algorithm in sender. The GA-Fuzzy controller can improve the adaptability and flexibility of the primal algorithm, so the aggregative data flow in bottleneck link does not exceed the link capacity even though the bottleneck link capacity changes. Sixthly, a decentralized optimal control framework is given based on network congestion control problem. The framework can solve the optimal control allocation problem by decentralized method. Many applications such as product-consume problem or coordination problem can be taken as one of the optimal control allocation problems. Under the framework, the design of the decentralized control scheme is given. The framework can be extended to solve general large-scale optimal problem with decentralized method. Finally, the obtained results are summarized and future work is addressed.
修改评论