NN based ATM cell scheduling with queue length-based priorityscheme

The asynchronous transfer mode (ATM) is the choice of transport mode for broadband integrated service digital networks (B-ISDNs). We propose a window-based contention resolution algorithm to achieve higher throughput for nonblocking switches in ATM environments. In a nonblocking switch with input queues, significant loss of throughput can occur due to head-of-line (HOL) blocking when first-in first-out (FIFO) queueing is employed. To resolve this problem, we employ bypass queueing and present a cell scheduling algorithm which maximizes the switch throughput. We also employ a queue length based priority scheme to reduce the cell delay variations and cell loss probabilities. With the employed priority scheme, the variance of cell delay is also significantly reduced under nonuniform traffic, resulting in lower cell loss rates (CLRs) at a given buffer size. As the cell scheduling controller, we propose a neural network (NN) model which uses a high degree of parallelism. Due to higher switch throughput achieved with our cell scheduling, the cell loss probabilities and the buffer sizes necessary to guarantee a given CLR become smaller than those of other approaches based on sequential input window scheduling or output queueing