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Summary: 1
Neural Network Based Model Reference Controller
for Active Queue Management of TCP Flows
Kourosh Rahnami, Payman Arabshahi, Andrew Gray
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, CA 91109
{rahnamai,payman,gray}@jpl.nasa.gov
Abstract--We discuss here, implementation of a Neural
Network (NN) based Model Referenced Control (MRC)
algorithm to improve transient and steady state behavior of
Transmission Control Protocol (TCP) flows and Active
Queue Management (AQM) routers in a network setting.
Based on a fluid theoretical model of a network, two neural
networks are trained to control the traffic flow of a
bottleneck router. Results show dramatic improvement of
the transient and the steady state behavior of the queuing
window length. The results are compared to the traditional
RED algorithm and the P and PI controllers of classical
control theory.
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