Neural Network Design of a Banyan Network Controller

Brown, T.X
Liu, K.H.

IEEE Journal on Selected Areas in Communication, Vol. 8, No. 8, pp.
1428--1438. 1990

Abstract:
Packet switching networks require queueing due to output blocking that
is unavoidable. If internal blocking is also present, such as with the
Banyan switching network, then longer queues can be expected. The
algorithm for choosing nonblocking sets of data cells from the queues
can significantly affect the throughput and queueing behavior. We
present an algorithm that we show to have maximum throughput. Using a
novel equivalence class approach, we reduce this algorithm on a Banyan
network to a constraint satisfaction problem. To gain the required
computational speed, we use the massive parallelism of neural networks.
A neural network design is defined using multiple overlapping
winner-take-all circuits. This is shown to be stable and only result in
nonblocking sets of data cells. An efficient interface between the
neural network and the queue is also defined. The performance of the
Banyan with a neural network controller is compared to a
noninternal-blocking switch with various controllers, Surprisingly, the
Banyan is within a factor of two of the non-blocking switch.