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Proceedings Paper

Neural-network-based multistage interconnection network routing
Author(s): Venkatnarayan Krishnamoorthy; Yi Pan; Yanqing Zhang
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Paper Abstract

Techniques based on neural networks can provide efficient solutions to a wide variety of problems in computer science. Routing in computer networks is to schedule messages and select communication links so that messages can be transferred efficiently between source and destination processors. Finding an optimal solution to many routing problems usually reqrueis exponential time and is impractical in reality. Hence, many heuristic algorithms have been designed to find sub-optimal solutions. In this research we use neural networks with a set of constraints to capture various collisions in multistage interconnection networks (MINs). Our simulation results have indicated that the Hopfield neural network can be used to routing to avoid link collisions in electronic MINs and crosstalks in optical MINs.

Paper Details

Date Published: 4 August 2003
PDF: 4 pages
Proc. SPIE 5103, Intelligent Computing: Theory and Applications, (4 August 2003); doi: 10.1117/12.485695
Show Author Affiliations
Venkatnarayan Krishnamoorthy, Georgia State Univ. (United States)
Yi Pan, Georgia State Univ. (United States)
Yanqing Zhang, Georgia State Univ. (United States)

Published in SPIE Proceedings Vol. 5103:
Intelligent Computing: Theory and Applications
Kevin L. Priddy; Peter J. Angeline, Editor(s)

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