Neural networks for routing communication traffic

Author

Rauch, Herbert E. ; Winarske, Theo

Author_Institution

Lockheed Palo Alto Res. Lab., CA, USA

Volume

8

Issue

2

fYear

1988

fDate

4/1/1988 12:00:00 AM

Firstpage

26

Lastpage

31

Abstract

The use of neural network computational algorithms to determine optimal traffic routing for communication networks is introduced. The routing problem requires choosing multilink paths for node-to-node traffic to minimize loss, which is represented by expected delay or some other function of traffic. The minimization procedure is implemented using a modification of the neural network traveling-salesman algorithm. Illustrative simulation results on a minicomputer show reasonable convergence in 250 iterations for a 16-node network with up to four links from origin to destination.<>

Keywords

graph theory; minimisation; neural nets; telecommunication networks; communication traffic; expected delay; loss minimization; multilink paths; neural network computational algorithms; node-to-node traffic; optimal traffic routing; traveling-salesman algorithm; Communication networks; Computer networks; Convergence; Delay; Microcomputers; Minimization methods; Neural networks; Routing; Telecommunication traffic; Traffic control;

fLanguage

English

Journal_Title

Control Systems Magazine, IEEE

Publisher

ieee

ISSN

0272-1708

Type

jour

DOI

10.1109/37.1870

Filename

1870