A High Throughput Packet-Switching Network with Neural Network Controlled Bypass Queueing and Multiplexing

This paper proposes a high throughput packet switching network with bypass queues based on a MIN. We improve the switch throughput by partitioning the input buffers into disjoint buffer sets and multiplexing several sets of nonblocking packets within a time slot. A neural network model is presented as a controller for packet scheduling and multiplexing in the switch.