Neural Network controller for rearrangeable switching networks

Young Keun Park, Vladimir Cherkassky

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


The rapid evolution in the field of communication networks requires high speed switching technologies. This involves a high degree of parallelism in switching control and routing performed at the hardware level. In this paper a neural network approach to controlling a three stage Clos network in real time is proposed. This controller provides optimal routing of communication traffic requests on a call-by-call basis by rearranging existing connections with a minimum length of rearrangement sequence so that a new blocked call request can be accommodated. The proposed neural network controller uses Paull's rearrangement algorithm, along with the special (least used) switch selection rule in order to minimize the length of rearrangement sequences. The functional behavior of our model is verified by simulations and it is shown that the convergence time required for finding an optimal solution is constant regardless of the switching network size. The performance is evaluated for random traffic with various traffic loads. Simulation results show that applying the least used switch selection rule increases the efficiency in switch rearrangements, reduces the network convergence time and also keeps the network from being trapped in local minima. The implementation aspects are also discussed to show the feasibility of the proposed approach.

Original languageEnglish (US)
Title of host publication1993 IEEE International Conference on Neural Networks
PublisherPubl by IEEE
Number of pages6
ISBN (Print)0780312007
StatePublished - Jan 1 1993
Event1993 IEEE International Conference on Neural Networks - San Francisco, California, USA
Duration: Mar 28 1993Apr 1 1993

Publication series

Name1993 IEEE International Conference on Neural Networks


Other1993 IEEE International Conference on Neural Networks
CitySan Francisco, California, USA


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