A proposal for a semi-dynamically reconfigurable optical network optimization

The Routing and Wavelength Assignment (RWA) problem has attracted lots of attention in the research field for the past decade. Most of the existing works are the classic static RWA problem, which assumes every time for the reconfiguration, all the existing connections will be reconfigured. In a real operating network, the reconfiguration has to take the existing connections into consideration and any reconfiguration of the existing connection results in the disruption of the upper level traffic. The algorithms that are slow or do not consider the existing connections in the network cannot be used in the real-time reconfigurable network. In this paper, we propose the semi-dynamic/static network optimization problem that takes into consideration existing connections from the previous reconfiguration session. The objective function in the formulation is penalty-based, i.e., there are penalties for the reconfiguration of a connection, for the rejection of a connection demand and for the most congested link. Rules on the existing capacity and new demand in the new session are proposed. We have successfully used the Lagrange Relaxation (LR) and Subgradient Method to successfully solve this network optimization problem. This state-of-art frame work allows us to evaluate systematically some sample networks in terms of various network performances and behaviors. At the same time, excellent algorithm performance and efficient computation complexity are demonstrated.