Intelligent packet shaper to avoid network congestion for improved streaming video quality at clients

This paper proposes a traffic shaping algorithm based on neural networks, which adapts to a network over which streaming video is being transmitted. The pu’pose of this intelligent shaper being to eradicate all traffic congestion and improve the end-user$ video qualip. It possesses the capabilip to predict, to a very high level of accuracy, a siate of congestion based upon the training data collected about the network3 behavior. Initially the current traffic shaping technologies are discussed and later a simulation in a controlled environment is illustrated to exhilit the . effects of this intelligent traffic-shaping algorithm on the underlying network3 real time packet traffic and the eradication of unwanted abmptions in rhe streaming video$ qualiv. This paper concluded from the end results of the simulation that neural networks are a very superior means of modeling real-time traffic and that it can be applied as an appropriate solution to network congestion.