WDM rings are now capable of supporting more than 100 wavelengths over a single fiber. Conventional link and path formulations for the RWA problem are inefficient due to the inherent symmetry in wavelength assignment and the fact that the problem size increases fast with the number of wavelengths. Although a formulation based on maximal independent sets (MIS) does not have these drawbacks, it suffers from the exponential growth in the number of variables with the increasing network size. We develop a new ILP formulation based on the idea of partitioning the path set and representing the maximal independent sets in the original network using the independent sets calculated in each of these partitions. This formulation trades off the number of variables with the number of constraints and, as a result, achieves a much better scalability in terms of network dimension. The proposed approach is compared with existing formulations on ring networks of various sizes and it is demonstrated that the new formulation achieves more than two orders of magnitude decrease in running time, making it possible to (1) solve optimally large network instances for any number of wavelengths, which cannot be solved with classical formulations, and (2) perform extensive “what-if” analysis to evaluate the sensitivity of the optimal solutions to uncertainties in forecast traffic scenarios.

Power-awareness in networking attracts more attention as the trends in the energy consumption of the Internet raise growing concerns about the environmental impacts and sustainability of the network expansion. Building energy efficient equipment is definitely an integral part of the solution. However, such a strategy should be complemented with appropriate network protocols and routing methods to achieve maximum performance. In this paper, total power consumption of an optical WDM network is modeled in terms of the power consumed by individual lightpaths. The proposed model is then used to develop an ILP (Integer Linear Programming) formulation of the grooming problem. The exact solution of the formulation on a small network indicates that significant energy savings can be achieved with power efficient grooming.

Increasing demand for bandwidth and proliferation of packet based traffic represent a challenge for today's metro networks, which have been traditionally designed to carry circuit- switched connections. The problem is further complicated by the constraints of cost efficiency and traffic adaptability, imposed by the limited customer base in the metro area. Recently, several architectures have been proposed for future metro access networks. Nearly all of these solutions support dynamic reconfigurability, however reconfiguration policies have not been fully explored yet. In this paper, reconfiguration policies for IP/WDM metro access networks with switching delays are considered, where dynamic reconfiguration corresponds to dynamic allocation of wavelengths to access nodes. Exact formulation of the dynamic wavelength allocation (DWA) problem is developed as a Markov Decision Process (MDP) and a new cost function is proposed to attain both throughput efficiency and fairness. For larger problems, a heuristic approach based on first passage probabilities is developed and shown to yield nearly optimum performance through simulations.

In this paper we study traffic engineering of restorable paths in multiprotocol label switching (MPLS) networks. We consider off-line computation of working and restoration paths with path rerouting as the restoration scheme. First we compute a link-disjoint path set for given set of demands. Using this path set we study four approaches for selecting working and restoration paths, and formulate each method as an integer linear programming (ILP) problem. A traffic uncertainty model is developed in order to compare these approaches based on their robustness with respect to changing traffic patterns. We obtain numerical results and compare these design approaches based on the number of additional demands carried and the distribution of residual capacity over the network.