Community detection and infrastructure criticality

Infrastructure networks evolve according to societal needs: clusters of elements are found in regions where the demand for service is higher, while the system is sparser in areas of lower activity. These clusters are defined network communities, in analogy with human communities. A community detection algorithm is used here to obtain information at different levels of description. Communities are functional subsystems within the network, but the elements critical to their performance are not always detected by global analyses. To overcome this limitation, community centrality, a modified formulation of information centrality, is introduced. A new metric, cross-scale centrality, is also developed to reconcile information obtained at different scales of analysis. A model of the UK railway network is used as a case study: the results obtained from the examination of its community structure are used in conjunction with system-wide metrics to paint a richer picture of its vulnerability.