Adaptive Generalized Predictive Control of Active Queue Management in TCP Networks

This paper develops methodology and technique for the design, analysis, and implementation of an adaptive generalized predictive controller (AGPC) for active queue management in TCP networks. The TCP/AQM dynamic is modeled experimentally as a second-order system with a time delay where its parameters are estimated using the standard gradient algorithm. Based on this model, an AGPC is designed to gain the set-point tracking and robustness. AGPC, as a queue-based control mechanism, responds quickly to traffic changes, thus allowing for high utilization and small loss. We illustrate our results using ns-2 simulations and demonstrate the practical impact of adaptive model reference control on managing queue utilization and delay