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This thesis focuses on the survivable routing problem in WDM mesh networks where the objective is to minimize the total number of wavelengths used for establishing working and protection paths in the WDM networks. The past studies for survivable routing suffers from the scalability problem when the number of nodes/links or connection requests grow in the network. In this thesis, a novel path based shared protection framework namely Inter-Group Shared protection (I-GSP) is proposed where the traffic matrix can be divided into multiple protection groups (PGs) based on specific grouping policy. Optimization is performed on these PGs such that sharing of protection wavelengths is considered not only inside a PG, but between the PGs. Simulation results show that I-GSP based integer linear programming model, namely, ILP-II solves the networks in a reasonable amount of time for which a regular integer linear programming formulation, namely, ILP-I becomes computationally intractable. For most of the cases the gap between the optimal solution and the ILP-II ranges between (2-16)%. The proposed ILP-II model yields a scalable solution for the capacity planning in the survivable optical networks based on the proposed I-GSP protection architecture.

This thesis focuses on the survivable routing problem in WDM mesh networks where the objective is to minimize the total number of wavelengths used for establishing working and protection paths in the WDM networks. The past studies for survivable routing suffers from the scalability problem when the number of nodes/links or connection requests grow in the network. In this thesis, a novel path based shared protection framework namely Inter-Group Shared protection (I-GSP) is proposed where the traffic matrix can be divided into multiple protection groups (PGs) based on specific grouping policy. Optimization is performed on these PGs such that sharing of protection wavelengths is considered not only inside a PG, but between the PGs. Simulation results show that I-GSP based integer linear programming model, namely, ILP-II solves the networks in a reasonable amount of time for which a regular integer linear programming formulation, namely, ILP-I becomes computationally intractable. For most of the cases the gap between the optimal solution and the ILP-II ranges between (2-16)%. The proposed ILP-II model yields a scalable solution for the capacity planning in the survivable optical networks based on the proposed I-GSP protection architecture.