Abstract
Wavelength division multiplexing (WDM) technology has been widely applied to increase the capacity of existing SDH/SONET self-healing rings. As the number of wavelengths goes up to several dozens, SDH/SONET add-drop multiplexers (ADMs) become the dominant cost factor in network deployment. Traffic grooming studies how to arrange the placement of ADMs intelligently on wavelengths so as to reduce the number of ADMs required. We address traffic grooming in SDH/SONET WDM rings featuring an evolutionary approach. By showing that traffic grooming can be formulated as standard combinatorial optimization problems, we propose hybrid genetic algorithms (GAs) for the problem. Our algorithms can be applied to traffic grooming assuming arbitrary traffic patterns. Numerical results are reported on the performance of our grooming algorithms, which demonstrate performance better than greedy heuristics proposed in literature and comparable to a simulated-annealing (SA) based heuristic.
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