Improving RED by a neuron controller

Authors:
Jinsheng Sun;Moshe Zukerman
Affiliations:
The ARC Special Research Centre for Ultra-Broadband Information Networks, Department of Electrical and Electronic Engineering, The University of Melbourne, Victoria, Australia;The ARC Special Research Centre for Ultra-Broadband Information Networks, Department of Electrical and Electronic Engineering, The University of Melbourne, Victoria, Australia
Venue:
ITC20'07 Proceedings of the 20th international teletraffic conference on Managing traffic performance in converged networks
Year:
2007

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Abstract

In this paper, we propose a novel active queue management (AQM) algorithm called Neuron Control RED (NC-RED) that overcomes the drawbacks of the original RED. NC-RED uses a neuron controller to adaptively adjust the maximum drop probability to stabilize the average queue length around the target queue length. We demonstrate by simulations that NC-RED maintains stable operation independent of traffic loading, round trip propagation delay, and bottleneck capacity. We also demonstrate that NC-RED is robust to non-responsive UDP traffic and HTTP traffic, and it is effective for networks with multiple bottlenecks. Comparison with other well-known AQM algorithms like PI, REM and ARED demonstrates the superiority of NC-RED in achieving faster convergence to queue length target and smaller queue length jitter.