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A Spare Capacity Planning Methodology for Wide Area Survivable Networks

In this dissertation, a new spare capacity planning methodology is proposed utilizing path restoration. The approach is based on forcing working flows/traffic which are on paths that are disjoint to share spare backup capacity. The algorithm for determining the spare capacity assignment is based on genetic algorithms and is capable of incorporating non-linear variables such as non-linear cost function and QoS variables into the objective and constraints. The proposed methodology applies to a wider range of fault scenarios than most of the current literature. It can tolerate link-failures, node-failures, and link-and-node failures. It consists of two stages: the first stage generates a set of network topologies that maximize the sharing between backup paths by forcing them to use a subset of the original network. The second stage utilizes a genetic algorithm to optimize the set of solutions generated by the first stage to achieve an even better final solution. It can optimize the solution based on either minimizing spare capacity or minimizing the total network cost. In addition, it can incorporate QoS variables in both the objective and constraints to design a survivable network that satisfies QoS constraints. Dr. David Tipper Research Advisor