Managing Internet routers congested links with a Kohonen-RED queue
Engineering Applications of Artificial Intelligence
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Queue length oscillation at a congested link causes many undesirable properties such as large delay jitter, underutilization of the link and packet drops in burst. The main reason of this oscillation is that most queue management schemes determine the drop probability based on the current traffic without consideration on the impact of that drop probability on the future traffic. In this paper, we propose a new active queue (AQM) scheme to reduce queue oscillation and realize stable queue length. The proposed scheme measures the current arrival and drop rates, and uses them to estimate the next arrival rate. Based on this estimation, the scheme calculates the drop probability which is expected to realize stable queue length. We present extensive simulation with various topologies and offered traffic to evaluate performance of the proposed scheme. The results show that the proposed scheme remarkably reduces queue length oscillation compared to other well-known AQMs. It is also shown that the proposed scheme improves fairness among TCP flows due to the stable drop probability, and maintains high utilization with small queue length.