Optimization of spare capacity in WDM networks for real-time service restoration

In the case of network malfunction a network with restoration capability requires spare capacity to be used. Optimization of the spare capacity in this case is to find the minimum amount of spare capacity for the network to survive from network component failures. In this paper, the optimization of the spare capacity problem is investigated for the wavelength division multiplexing (WDM) mesh networks without wavelength conversion. To minimize the spare capacity, we will optimize both the routing and the wavelength assignment. This combinatorial problem is usually called the routing and wavelength assignment (RWA) problem and it is well known to be NP-hard. We give an integer linear programming (ILP) formulation for the problem. Due to the excessive run-times of the ILP, we propose a hybrid genetic algorithm approach (GA) for the problem. For benchmarking purpose, simulated annealing (SA) and Tabu search (TS) are also applied to this problem. To validate the effectiveness of the proposed method, the approach is applied to the China network, which has a more complicated network topology. Simulation results are very favorable to the GA approach.