We present algorithms that compute the routing and wavelength assignment (RWA) for scheduled lightpath demands in a wavelength-switching mesh network without wavelength conversion functionality. Scheduled lightpath demands are connection demands for which the setup and teardown times are known in advance. We formulate separately the routing problem and the wavelength assignment problem as spatio-temporal combinatorial optimization problems. For the former, we propose a branch and bound algorithm for exact resolution and an alternative tabu search algorithm for approximate resolution. A generalized graph coloring approach is used to solve the wavelength assignment problem. We compared the proposed algorithms to an RWA algorithm that sequentially computes the route and wavelength assignment for the scheduled lightpath demands.

We investigate the problem of routing a set of lightpath demands for which the start and end dates may be planned. We call this type of requests foreseeable lightpath demands or FLDs. In a transport network, FLDs correspond, for example, to clients' requests for pre-provisioned bandwidth capacity such as fixed-bandwidth pipes for bulk data transfers during the night, extra VPN bandwidth used during peak office working time, etc. Since in some cases the FLDs are not all simultaneous in time, it is possible to reuse physical resources to realize time-disjoint demands. We propose a routing algorithm that takes into account this property to minimize the number of required WDM channels in the physical links of the network. The gain (in term of saved resources) provided by the algorithm, when compared to a shortest path routing strategy, depends both on the spatial and temporal structure of the set of traffic demands and on the structure of the physical network. The routing problem is formulated as a combinatorial optimization problem. A tabu search meta-heuristic algorithm is developed to solve this problem.