Packet switching networks traffic prediction based on radial basis function neural network

Zaleski, ArkadiuszKacprzak, Tomasz2015-06-032015-06-032010Journal of Applied Computer Science., 2010 Vol.18 nr 2 s.91-101 sum.1507-03600000028431http://hdl.handle.net/11652/449New multimedia applications require Quality of Service support, which is still not successfully implemented in current packet-switched networks implementations. This paper presents a concept of neural network predictor, suitable for prediction of short-term values of traffic volume generated by end user. The architecture is Radial Basis Function neural network, optimized with respect to a number of neurons. Testing mode of the neural network is very fast, what enables application of this tool in nodes of telecommunication network. This would help to warn a network management system on early symptoms of congestion expected in the near future and avoid the network overload.application/pdfenPacket switching networks traffic prediction based on radial basis function neural networkArtykuł