The Research On The Congestion Control Method Of ABR Traffic

Integrated Service Digital Network(ISDN) is considered as the tendency of the communication technique in the future. Asynchronous Transfer Mode(ATM) is adopted as a typical technique by the International Telecommunication Union(ITU) and is spreaded . But the loss of data and the congestion of information are main reasons that affect the quality of service. ABR service is the only one type of traffic that can be controlled using the feedback mechanism. So, in the recent, the control and management of ABR service becomes a hot subject. The communication network is a large and hybrid system, the research on congestion control of ATM network has great significance in theory and practice. The paper is just based on it and the control theory is used to solve the congestion of controllable flow.The paper begins with the foundation of ATM network, and introduces the basic work principle of networks and the feedback mechanism. Then, the model of single bottleneck node is set up and the PID control method is introduced into the net control based on the model. The controller for the special network model is designed and the sufficient condition is given which can guarantee the stability of closed loop. The feed-forward control is adopted to reduce the effect caused by oscillation of available bandwidth. To remove the effect of the saturation feature of the queue length, the virtual queue is set in the switch. At last, the increase factor and decrease factor are utilized to quicken the response. All the method mentioned above can keep the queue output stable.Delay variation and oscillation of available bandwidth are two important elements that affect the stability and dynamic performance of the system. Two improved methods are presented base on the existing literature. They solve the problem of ABR congestion control using the inner model control and Smith predictor, respectively. The system can keep the queue length stable in a certain region when the available bandwidth has large oscillation.In the final, the intelligent control method of neural network is introduced in the congestion control of network. The neural network can realize theprediction of available bandwidth, the modeling of queuing model of the switch and the queue control. The predictive networks can achieve the accurate predicted value for the processes such as ARMA and FARIMA time sequence. Based on it, the PERICA algorithm, neural network control algorithm and fairness algorithm achieve better control performance.