A neural network model for traffic controls in multistage interconnection networks

Nobuo Funabiki, Yoshiyasu Takefuji, Kuo Chun Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Summary form only given, as follows. A neural network model for traffic controls in multistage interconnection networks is discussed. The goal of the neural network model is to find conflict-free traffic flows to be transmitted among given I/O traffic demands in order to maximize the network throughput. The model requires n2 processing elements for the traffic control in an n × n multistage interconnection network. The model runs not only on a sequential machine but also on a parallel machine with maximally n2 processors. The model was verified by solving ten 32 × 32 network problems.

Original languageEnglish
Title of host publicationProceedings. IJCNN - International Joint Conference on Neural Networks
Editors Anon
PublisherPubl by IEEE
Number of pages1
ISBN (Print)0780301641
Publication statusPublished - 1992 Jan 1
Externally publishedYes
EventInternational Joint Conference on Neural Networks - IJCNN-91-Seattle - Seattle, WA, USA
Duration: 1991 Jul 81991 Jul 12

Publication series

NameProceedings. IJCNN - International Joint Conference on Neural Networks

Other

OtherInternational Joint Conference on Neural Networks - IJCNN-91-Seattle
CitySeattle, WA, USA
Period91/7/891/7/12

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint

Dive into the research topics of 'A neural network model for traffic controls in multistage interconnection networks'. Together they form a unique fingerprint.

Cite this