Correlation analysis of complex network metrics on the topology of the Internet

We present an experimental study on the linear relationship between a rich set of complex network metrics, to methodologically select a subset of non-redundant and potentially independent metrics that explain different aspects of the topology of the Autonomous System view of the Internet. We followed a data-driven approach based on (1) a correlation study of different properties of evolving Internet networks, and (2) the validation of a non-redundant set of metrics by evaluating the performance of supervised and unsupervised machine learning techniques. We confirm pair-wise metric correlations observed in other types of networks and identify sets of highly correlated metrics that may reveal patterns specific to the topology of the Internet.