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The recently proposed neural network rate control (NNRC) framework that achieves queueing delay and queue length regulation, is expanded to further guarantee fair allocation of network resources among competing sources. This is possible by introducing a novel algorithm that controls in a stable and adaptive manner the number of communication channels in each source. Simulation studies performed on...
In this paper we design a neuro-adaptive congestion control system, via regulating the packet round trip time for each user application, without violating a maximum cost per packet value, prescribed by the user. Reliable desired round trip values are provided via a neural net estimator, which consequently are utilized for the design of a neural network rate controller. To improve the achievable application...
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...
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