In this paper we present a hierarchical loss network model for estimatingthe end-to-end blocking probabilities for large networks.

As networks grow in size, nodes tendto form clusters geographically and hierarchical routing schemes are morecommonly used. Loss network and reduced load models are often used toapproximate end-to-endcall blocking probabilities, and hence, throughput. However so far all workbeing done in this area is for flat networks with flat routing schemes.

We aim at developing a more efficient approximation method for networksthat have a natural hierarchy and/or when some form of hierarchical routingpolicy is used. We present two hierarchical models in detail for fixedhierarchical routing and dynamic hierarchical routing policies,respectively, via the notion of network abstraction, route segmentation, traffic segregationand aggregation. Computation is done separately within each cluster (local)and among clusters (global), and the fixed point is obtained by iterationbetween local and global computations. We also present numerical resultsfor the first case.