A self-tuning controller for queuing delay regulation in TCP/AQM networks

Abstract

AQM router aims primarily to control the network congestion through marking/dropping packets which are used as congestion feedback in traffic sources to balance their flow rate. However, stabilizing queuing delay and maximizing link utilization have been considered as the main control objectives, especially in media dominated networks. Usually, most of the AQM algorithms are designed for a nominal operating point. However, time-varying nature of network parameters frequently violates their robustness bounds. In this paper, a self-tuning compensated PID controller is proposed to address the time-varying nature of network conditions caused by parameter variations and unresponsive connections. The proposed scheme consists of network parameter estimation and a self-tuning AQM. Traffic load, network delay, and bottleneck link capacity are the time-varying network parameters whose variation effects should be compensated by the controller gains adaptation. As the controller gains are simply and directly obtained from the dynamic model, the obtained self-tuning controller can reasonably adapt itself to different operating conditions, while preserving the simplicity of the PI controllers. Packet-level simulations using ns2 show the outperformance of the developed controller for both latency regulation and resource utilization.