Two-stage uncertainty incorporating in optical core networks
In guaranteed-type applications the bandwidth planning and cost management are two important issues in deployment of optical core networks. A two-stage fuzzy-based approach is proposed for accommodating long-term demand uncertainties in dense wavelength division multiplexing optical networks. Here, the uncertainties are modelled using the Gaussian fuzzy membership functions. First, the forecasted part of demand matrix is introduced to Dijkstra shortest path-based routing algorithm. Then, the available wavelengths are assigned to demand uncertainties. Unlike existing algorithms, different bandwidth cost factors are assigned to the links of a lightpath according to network and links state information. The performance of proposed approach is evaluated on a typical optical link for uncertain traffic loads in Erlang mode. Simulation results show that the proposed fuzzy-based approach is up to 29% cost-effective for accommodating network demands in real-world applications comparing to existing algorithms.
