Various static resource allocation algorithms have been used in WDM networks to allocate resources such as wavelength channels, transmitters, receivers, and wavelength converters to a given set of static lightpath demands. However, although optimized resource allocations can be obtained, it remains an open issue how to determine which resources are the bottlenecks in achieving better performance. Existing static resource allocation algorithms do not explicitly measure the impact of changes of network resources or lightpath demands on the design objective. We propose such a measurement based on the Lagrangian relaxation framework. We use the optimized values of Lagrange multipliers as a direct measurement of the criticality of resources. Such a quantitative measurement can be naturally acquired along with the optimization process to obtain the optimal solution (or a near-optimal solution) to the static routing and wavelength assignment problem. We investigate three practical applications of the resource criticality (RC) analysis in WDM network planning. In the first application, we use our proposed measurement to identify critical resources and thus to decide the best way to add or reallocate resources. In the second application, we estimate the impact of the addition or removal of lightpath demands on the design objective. This kind of estimation helps to set a proper price for lightpath demands. In the third application, the results of the RC analysis are used to speed up the convergence of the optimization process for different network scenarios.
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