Neural network implementation of the shortest path algorithm for traffic routing in communication networks

Stelios C.A. Thomopoulos*, Lei Zhang, Chin Der Wann

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

A neural network computation algorithm is introduced to solve for the optimal traffic routing in a general N-node communication network. The algorithm chooses multilink paths for node-to-node traffic which minimize a certain cost function. Unlike the algorithm introduced earlier in this area, knowledge of the number of links between each origin-destination pair is not required by the algorithm, therefore it can be applied to variable-length path routing problems. The neural network structure for implementing the algorithm is a modified form of the one used by the traveling salesman algorithm. Computer simulation in a nine- and sixteen-node grid network showed that the algorithm performs extremely well in single and multiple paths.

Original languageEnglish
Title of host publication91 IEEE Int Jt Conf Neural Networks IJCNN 91
PublisherPubl by IEEE
Pages2693-2702
Number of pages10
ISBN (Print)0780302273
StatePublished - 1991
Externally publishedYes
Event1991 IEEE International Joint Conference on Neural Networks - IJCNN '91 - Singapore, Singapore
Duration: 18 11 199121 11 1991

Publication series

Name91 IEEE Int Jt Conf Neural Networks IJCNN 91

Conference

Conference1991 IEEE International Joint Conference on Neural Networks - IJCNN '91
CitySingapore, Singapore
Period18/11/9121/11/91

Fingerprint

Dive into the research topics of 'Neural network implementation of the shortest path algorithm for traffic routing in communication networks'. Together they form a unique fingerprint.

Cite this