se, there is no topology problem, since the mesh topology at the physical level is simply given from the set of nodes and WDM links that are deployed. For a mesh network, in the case of static traffic, the optimization algorithm that is used to design the layer is based on integer linear programming (ILP). This method has been widely used in several network optimization problems [69,71] and results to be a very good compromise between effective optimization and computational complexity. We will return on that in Chapter 9 where we will describe in detail a dimensioning method for Automatically Switched Optical Networks/Generalized Multi-Protocol Label Switching (ASON/GMPLS) networks based on ILP. Moreover, widely proved libraries exist for ILP optimization SO that software develop- ment is also less prone to unresolved bugs. In order to set up the network with dynamic traffic, first we dimension the network as if the traffic would be static using a traffic forecast derived from the dynamic traffic model. In order to route the capacity requests while they are dynamically presented to the considered layer, we have used a simple derivate of the Open Shortest Path First (OSPF) algorithm. In particular, the weight of a path is set equal to the cost of the resources used for routing the trail along that path. Periodically, a network opti- mization is carried out on the working network simulating a sort of centralized traffic engineering. As a matter of fact, also in this simulated case, the continuous use of OSPF risks taking the network further and further from the optimum, due to the fact that local and not global optimization is performed. Traffic engineering is carried out with an ILP algorithm very similar to that used for static traffic. The main modification is the addition of another weight to the value of the final solution, that is, the number of trails to reroute with respect to the field situation; this is done SO to select, among those solutions with a similar cost, the solution rerouting the smallest poss