A robust proportional controller for AQM based on optimized second-order system model

Active Queue Management (AQM) is an effective mechanism to improve the performance of end-to-end congestion control. However, existing AQM schemes are sensitive to network traffic changes. In this paper, we propose a novel AQM algorithm based, for the first time, on the optimized second-order system model, called Adaptive Optimized Proportional Controller (AOPC). AOPC measures the latest packet loss ratio, and uses it as a complement to queue length in order to dynamically adjust packet drop probability. Through using TCP throughput model, AOPC is capable of detaching from the number of TCP sessions N and insensitive to various network conditions. The parameter tuning rule is in compliance with the optimized second-order system model which has a small overshoot and fast convergence speed. We comprehensively evaluate the performances of AOPC through extensive simulations using NS2 simulator, and contrast it with previous approaches such as REM, PI, PID, PIP, and LRED. Simulation results demonstrate that AOPC is more responsive to time-varying network conditions than other algorithms, and obtains the best tradeoff between utilization and delay.