Abstract
In this paper, we propose a parallel QoS scheduler for a WDM optical
interconnection system (WOPIS), using a new ranked Hopfield neural-network
(RHNN). The WOPIS contains a set of Clos-like optical switches and a handful
of output FDL-based optical buffers. The RHNN scheduler determines an
optimal set of neurons (I/O paths) to be enabled, achieving maximal system
throughput and priority differentiation subject to the switch- and
buffer-contention-free constraints. Structured with ranked neurons, the RHNN
allows higher-rank neurons (higher-priority and/or lower-delay paths) to
disable lower-rank neurons that have been enabled during previous
iterations. Ranking the neurons unfortunately gives rise to a convergence
problem. We present two theorems that give the sufficient conditions for the
RHNN scheduler to converge to the optimal solution. We demonstrate via
simulation results that, with the computation time within one system slot
time, the RHNN scheduler achieves near 100% throughput and multi-level
prioritized scheduling.
© 2011 IEEE
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