Neural network-based real-time dynamic nonhierarchical network routing for B-ISDN

Author

Nan, Hua ; Liu, Zemin

Author_Institution

Beijing Univ. of Posts & Telecommun., China

Volume

1

fYear

1997

fDate

9-12 Jun 1997

Firstpage

153

Abstract

We propose a neural network method for B-ISDN real-time dynamic nonhierarchical network routing in this paper. This method can optimize routing according to VCC request and resource of network, balance average call blocking rate and average routing distance of a global network, and reduce average call setup time. We give the routing algorithm and energy function of the Hopfield neural network. Finally, our simulation results show that the proposed neural network method is very effective

Keywords

B-ISDN; Hopfield neural nets; asynchronous transfer mode; graph theory; optimisation; telecommunication computing; telecommunication congestion control; telecommunication network routing; B-ISDN; Hopfield neural network; VCC request; average call blocking rate; average call setup time; average routing distance; global network; neural network-based real-time dynamic nonhierarchical network routing; Asynchronous transfer mode; B-ISDN; Bandwidth; ISDN; Network topology; Neural networks; Optimization methods; Routing; Telecommunication network topology; Virtual colonoscopy;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks,1997., International Conference on

Conference_Location

Houston, TX

Print_ISBN

0-7803-4122-8

Type

conf

DOI

10.1109/ICNN.1997.611655

Filename

611655