| Summary: | Optical networks are essential in today’s global communications, and the study of planning tools that efficiently allocate network resources is crucial to network providers. The assignment of wavelengths, alongside routing, are critical functions in all optical network planning tools. This dissertation focuses on the study of wavelength assignment algorithms based on Graph Coloring techniques. In this dissertation, we analyse the performance of the usual Greedy heuristic, a well-known Graph Coloring heuristic applied to optical network planning, as well as the Degree of Saturation (DSATUR) and Recursive Largest First (RLF) heuristics, in several real net- work scenarios. These last two heuristics, to the best of our knowledge, have not yet been applied in the context of optical networks. Extensive simulations have been performed, using real network topologies, such as COST 239, and CONUS networks, considering a full mesh logical topology, and we conclude that DSATUR and RLF heuristics can out-perform Greedy heuristic in network scenarios where there are several network clusters interconnected by only one or two links. In these cases, the RLF and DSATUR heuristics provide less 9 and 5 wavelengths respectively than the Greedy heuristic. Despite generating fewer wavelengths, we have verified that these heuristics need a higher computing time than the Greedy heuristic. Besides these heuristics, the traditional First Fit and Most-Used heuristics were also studied, and lead to performance similar to the Greedy heuristics.
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