Access control for MPEG video applications using neural network and simulated annealing (Q2566900)

Summary: We present a dynamic model for access control mechanism used in computer communication network applied to MPEG video transmission over Internet. This model is different from those developed in the previous works related to this topic. In our model, token buckets supported by data buffers are used to shape incoming traffic and one multiplex or, serving all the token pools, multiplexes all the conforming traffic. The model is governed by a system of discrete nonlinear difference equations. We use neural network as the feedback controller which receives at its input (measurable) available information and provides at its output the optimal control. The simulated annealing algorithm is used to optimize the system performance by adjusting the weights. For illustration, we present numerical results which show that the system performance of MPEG video server can be improved by using neural network and simulated annealing approach.