Self-organizing maps
The Handbook of Brain Theory and Neural Networks
The Handbook of Brain Theory and Neural Networks
Analysis of Queueing Networks with Blocking
Analysis of Queueing Networks with Blocking
Fundamentals of Queueing Theory
Fundamentals of Queueing Theory
Activities on next-generation networks under Global Information Infrastructure in ITU-T
IEEE Communications Magazine
Performance evaluation of multi-service UMTS core networks with clustering and neural modelling
International Journal of Mobile Network Design and Innovation
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This paper is devoted to modeling and simulation of traffic with integrated services at media gateway nodes in the next generation networks, based on Markov reward models MRM. The bandwidth sharing policy with the partial overlapped transmission link is considered. Calls arriving to the link that belong to VBR and ABR traffic classes, are presented as independent Poisson processes and Markov processes with constant intensity and/or random input stream, and exponential service delay time that is defined according to MRM. Traffic compression is calculated using clustering and learning vector quantification e.g., self-organizing neural map. Numerical examples and simulation results are provided for communication networks of various sizes. Compared with the other methods for traffic compression calculations, the suggested approach shows substantial reduction in numerical complexity.