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 - Jan 1 1992
Externally publishedYes
EventInternational Joint Conference on Neural Networks - IJCNN-91-Seattle - Seattle, WA, USA
Duration: Jul 8 1991Jul 12 1991

Publication series

NameProceedings. IJCNN - International Joint Conference on Neural Networks

Other

OtherInternational Joint Conference on Neural Networks - IJCNN-91-Seattle
CitySeattle, WA, USA
Period7/8/917/12/91

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

    Funabiki, N., Takefuji, Y., & Lee, K. C. (1992). A neural network model for traffic controls in multistage interconnection networks. In Anon (Ed.), Proceedings. IJCNN - International Joint Conference on Neural Networks (Proceedings. IJCNN - International Joint Conference on Neural Networks). Publ by IEEE.