Evolutionary Genetic Approach for Prediction of the Bandwidth-Demand Patterns within a Vp

Virtual Path (VP) bandwidth control improves transmission efficiency in an ATM network. An accurate estimate of the bandwidth-demand within a VP leads to efficient VP bandwidth control. So far the statistical methods were employed to predict the bandwidth-demand. We present a scheme based on the Evolutionary Genetic Approach to predict the bandwidth-demand patterns in VPs. The efficiency of this approach, quantified in terms of the Degree of Learning (DoL), is evaluated through simulation and the results are presented. Simulation studies on the effectiveness of the EGA on an ATM network and their results were presented.