eral we would like to evidence three possible methods [21]: 1. A priori adjustment 2. A posteriori adjustment 3. Probabilistic approach In the first two methods, the idea is simply to use a safety margin to face possible fluc- tuations of the traffic matrix. This safety margin reflects at the end in an overdeploy- ment of network resources with respect to the optimum solution dictated by the average traffic matrix. The difference between the two methods is that in the first the average traffic matrix is augmented by the safety margin and then the optimization is carried out as usual. Telecommunication Networks In the second method all the optimization is carried out on the ground of the average traffic and at the end more resources are deployed with respect to the optimization out- put. The key issue in both these methods is how to choose the safety margin to be sure to reduce suitably the network rejection probability (that is, the probability a connection request is rejected by the network) while containing the deployment cost. A discussion based on statistical approach is reported in Ref. [21] where it is demon- strated that it is possible to select an optimum safety margin starting from hypothesis on the statistical distribution of the traffic both in a priori and in a posteriori adjustment. However, even when the margin is chosen in this way, in particular cases, its use leads to excessive overdeployment in some areas of the network where in other areas resource shortage could still happen for modest fluctuations of the traffic variables. Sometimes the problem is solved considering different safety margins in different zones of the network, but other times this gives no advantage. In any case, after the design of the network using the safety margin-driven overdeploy- ment, simulations have to be generally performed to verify the effectiveness of the design in reducing the rejection probability. Better results are achieved via the probabilistic method, which uses directly the knowl- edge of the traffic statis