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.
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Sun, J., Zukerman, M. (2007). Improving RED by a Neuron Controller. In: Mason, L., Drwiega, T., Yan, J. (eds) Managing Traffic Performance in Converged Networks. ITC 2007. Lecture Notes in Computer Science, vol 4516. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72990-7_40
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DOI: https://doi.org/10.1007/978-3-540-72990-7_40
Publisher Name: Springer, Berlin, Heidelberg
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