RBF-PID Based Adaptive Active Queue Management Algorithm for TCP Network

Active queue management (AQM) has been widely used for congestion avoidance in transmission control protocol (TCP) networks. Although numerous AQM schemes have been proposed to regulate a queue size close to a reference level, most of them are incapable of adequately adapting to TCP network dynamics due to TCP's non-linearity and time-varying stochastic properties. To alleviate these problems, we propose a novel adaptive AQM(active queue management ) algorithm for TCP network to cope with the network delay and time-varying network parameters based on RBF-PID controller, the RBF(redial basis function) neural network is employed to automatically tune the controller's parameters according to link capacity, traffic load and transmitting time-delay, which makes the presented AQM algorithm perform well for a wide-range of network conditions. The simulation results have shown that the RBF-PID-based AQM is feasible and efficient, and yields superior performance with faster transient time and better adaptive ability compared to the proportional-integral (PI)-based AQM.

[1]  Sheng Chen,et al.  A clustering technique for digital communications channel equalization using radial basis function networks , 1993, IEEE Trans. Neural Networks.

[2]  Richard J. Gibbens,et al.  Resource pricing and the evolution of congestion control , 1999, at - Automatisierungstechnik.

[3]  Martin May,et al.  Analytic evaluation of RED performance , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[4]  Fernando Paganini,et al.  Scalable laws for stable network congestion control , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[5]  QUTdN QeO,et al.  Random early detection gateways for congestion avoidance , 1993, TNET.

[6]  Steven H. Low,et al.  Analysis and design of AQM based on state-space models for stabilizing TCP , 2003, Proceedings of the 2003 American Control Conference, 2003..

[7]  Vishal Misra,et al.  Fluid-based analysis of a network of AQM routers supporting TCP flows with an application to RED , 2000, SIGCOMM.

[8]  Hitay Özbay,et al.  On the design of AQM supporting TCP flows using robust control theory , 2004, IEEE Transactions on Automatic Control.

[9]  James Aweya,et al.  A control theoretic approach to active queue management , 2001, Comput. Networks.

[10]  Donald F. Towsley,et al.  Analysis and design of controllers for AQM routers supporting TCP flows , 2002, IEEE Trans. Autom. Control..