Alessandro Chessa

Community core detection in transportation networks.

This work analyzes methods for the identification and the stability under perturbation of a territorial community structure with specific reference to transportation networks. We considered networks of commuters for a city and an insular region. In both cases, we have studied the distribution of commuters trips (i.e., home-to-work trips and vice versa). The identification and stability of the communities cores are linked to the land-use distribution within the zone system, and therefore their proper definition may be useful to transport planners.

Spatial correlations in attribute communities.

Community detection is an important tool for exploring and classifying the properties of large complex networks and should be of great help for spatial networks. Indeed, in addition to their location, nodes in spatial networks can have attributes such as the language for individuals, or any other socio-economical feature that we would like to identify in communities. We discuss in this paper a crucial aspect which was not considered in previous studies which is the possible existence of correlations between space and attributes. Introducing a simple toy model in which both space and node attributes are considered, we discuss the effect of space-attribute correlations on the results of various community detection methods proposed for spatial networks in this paper and in previous studies. When space is irrelevant, our model is equivalent to the stochastic block model which has been shown to display a detectability-non detectability transition. In the regime where space dominates the link formation process, most methods can fail to recover the communities, an effect which is particularly marked when space-attributes correlations are strong. In this latter case, community detection methods which remove the spatial component of the network can miss a large part of the community structure and can lead to incorrect results.

Distributed Generation and Resilience in Power Grids

We study the effects of the allocation of distributed generation on the resilience of power grids. We find that an unconstrained allocation and growth of the distributed generation can drive a power grid beyond its design parameters. In order to overcome such a problem, we propose a topological algorithm derived from the field of Complex Networks to allocate distributed generation sources in an existing power grid.

Complex Networks Analysis of Commuting

The emerging new science of networks is providing an elegant paradigm for the characterization of the broad area of complex systems. New research perspectives have been opened in the study of many real phenomena and processes, and recently fields like urban, regional, and environmental sciences have gained new insights from the tools provided by network science. The complex networks analysis (CNA) becomes a useful framework in these fields to disentangle problems of a complex and unpredictable nature.