s constitute a capacity to be routed through the network without the failed link. This can be done with an ILP algorithm to optimize the resources use. Generally the cost of the restoration part of the network has to be recalculated since the final solution will not coincide with one of the partial solutions. From a complexity point of view, it could seem that restoration design is much more complex than working capacity assignment, due to the fact that one ILP optimization is required for each network link. This is generally not true due to two facts: the first is that only the optical layer is involved in the routing, grooming is not permitted during this type of restoration to avoid multilevel signaling. Moreover, only a few elements of the traf- fic matrix are different from zero, contributing to lower computation complexity. 8.4.2.2.7 Restoration at GMPLS Layer The procedure is quite similar to that carried out for restoration in the optical layer, with the same three restoration types. The difference is that now there are the MPLS LSPs to be restored, SO that we have to face a two-layer optimization. This allows grooming to be used also when designing restoration resources generally with a better result with respect to the same restoration strategy adopted at the optical layer. On the other hand, the complexity of the whole design algorithm is quite higher. 8.4.2.2.8 Final Comment on Survivability Resources Design We have presented a set of methods to design survivability resources independently from working resources. This is for sure a suboptimum procedure, but as we have seen has a certain number of advantages. In any case, several optimization methods have been pro- posed in literature that does not divide the planning of working and survivability capac- ity. They are strictly related to a specific survivability method, but in principle, provide an optimum solution to the planning problem. Naturally, the complexity of such a design method is higher with respect to what we have used here and generally so