Bandwidth-demand prediction in virtual path in ATM networks using genetic algorithms

The concept of Virtual Paths (VP) is a powerful technique to improve the tr ansmission efficiency in ATM networks. Transmission efficiency can be impro ved by dynamically changing the bandwidths of the VPs, based on the demand. Intelligent controllers, which predict bandwidth-demand patterns to enable better VP management, have the potential to revolutionize ATM network perf ormance. We present a scheme based on the Evolutionary Genetic Approach to predict the bandwidth-demand patterns in VPs. The efficiency of this approa ch, quantified in terms of the Degree of learning (DoL), is evaluated throu gh simulation and the results are presented. (C) 1999 Elsevier Science B.V. All rights reserved.