A Neural Network Congestion Control Algorithm for the Internet

A new approach of controlling congestion in the Internet is proposed in this paper via regulating the round trip towards satisfying a user imposed desired sending time. For this purpose linear in the weights neural networks are employed to construct an on-line model for the estimated round trip depending on source rate (control input) and congestion level which is directly measured from the network via monitoring the state of the marking bit for each packet acknowledgement. When the network has enough resources (throughout the transmission period) to support the user requirement the neural network based rate control algorithm guarantees the uniform ultimate boundedness of the achieved round trip with respect to an arbitrarily small neighborhood of the desired round trip. In the unfortunate case of high congestion, the controller reduces the rate to the point of logical congestion levels. Simulation studies illustrate the approach, highlighting various performance measures (i.e. fairness, buffer level, source allocation) and verifying theoretical analysis