A geographic directed preferential internet topology model

The goal of this work is to model the peering arrangements between Autonomous Systems (ASes). Most existing models of the AS-graph assume an undirected graph. However, peering arrangements are mostly asymmetric customer–provider arrangements, which are better modeled as directed edges. Furthermore, it is well known that the AS-graph, and in particular its clustering structure, is influenced by geography.We introduce a new model that describes the AS-graph as a directed graph, with an edge going from the customer to the provider, but also models symmetric peer-to-peer arrangements, and takes geography into account. We are able to mathematically analyze its power-law exponent and number of leaves. Beyond the analysis, we have implemented our model as a synthetic network generator we call GdTang. Experimentation with GdTang shows that the networks it produces are more realistic than those generated by other network generators, in terms of its power-law exponent, fractions of customer–provider and symmetric peering arrangements, and the size of its dense core. We believe that our model is the first to manifest realistic regional dense cores that have a clear geographic flavor. Our synthetic networks also exhibit path inflation effects that are similar to those observed in the real AS graph.