Multi-Layer Network Design with Multicast Traffic and Statistical Multiplexing

The new packet services and applications are radically changing not only traffic demands but also the architecture of transport networks. Adding packet layer support into backbone nodes is considered an important opportunity by telecom carriers that want to integrate packet technologies of the access and metropolitan networks within their networks to improve efficiency and flexibility. In this context, Multi- Protocol Label Switching (MPLS) is at the moment the most promising and popular packet technology. The resulting new network architecture requires new models and methodologies for designing the network in a cost effective way. The classical network design approaches are no longer appropriate since they cannot capture the traffic aggregation effect due to the added packet layer and new multi-layer network design models must be adopted. In a previous work we proposed a mathematical programming model for the design of two-layers networks in the presence of point-to-point traffic demands. In this paper we extend the model to the case of multicast services which are becoming more and more popular due to IPTV applications. A MPLS layer is considered on top of a transport network (SDH or WDM depending on required link speed) and the conflicting effects of the additional cost of MPLS support in the nodes, and the cost saving due to traffic aggregation are taken into account in the models. Traffic aggregation allows to save bandwidth due to the statistical multiplexing and the granularity of capacity values available for links and nodes. We present a MIP (Mixed Integer Programming) model for the problem that aims at optimizing the number and location of MPLS nodes in the network and the link capacity dimensioning. The problem includes the minimum cost Steiner-tree problem as a special case and is, therefore, NP-hard. We propose a local search based heuristic. This algorithm provides reasonable good solutions in short computational time as shown by the computational results obtained for realistic instances.