Optimizing IP networks in a hybrid IGP/MPLS environment

In this paper, we consider a traffic engineering (te) approach toip networks in a hybridigp/mpls environment. Thoughigp (Interior Gateway Protocol) routing has proven its scalability and reliability, effective traffic engineering has been difficult to achieve in public IP networks because of the limited functional capabilities of conventionalip technologies.mpls (Multi-Protocol Label Switching) on the one hand enhances the possibility to engineer traffic onip networks by allowing explicit routes. But on the other hand it suffers from the scalability (n-square) problem. Hybridigp/mpls approaches rely onip native routing as much as possible and usempls only if necessary. In this work we propose a novel hybrid traffic engineering method based on genetic algorithms, which can be considered as an offlinete approach to handle long or medium-term traffic variations in the range days, weeks or months. In our approach the maximum number of hops anlsp (Label Switched Path) may take and the number oflsps which are applied solely to improve the routing performance, are treated as constraints due to delay considerations and the complexity of management. We apply our method to the German scientific network (b-win) for which a traffic matrix is available and also to some other networks with a simple demand model. We will show results comparing this hybridigp/mpls routing scenario with the result of pureigp routing and that of a full meshmpls with and without traffic splitting.