The structural analysis is the very basic tool for understanding the properties of a network. In this paper we present a (customizable) tool, able to compute in real-time the most important connectivity properties of a network, modeled as an undirected graph: connected and biconnected components, articulation points and bridges. The algorithm underlying the tool has been theoretically analyzed in the (semi-)streaming model, and has been tested with graphs up to hundreds of millions nodes and billions edges. The tool, therefore, can be employed to monitor traffic flows in medium and large networks, at real-time, and detect possible anomalies. As an application, we provide results about the structural properties of ten years of samples of the Autonomous System network, obtained from the Univ. of Oregon Route Views project, that (once again) shows the ubiquitous presence of power-law distribution.

Real-time Anomalies Detection and Analysis of Network Structure, with application to the Autonomous System Network.

LAURA, Luigi
2011-01-01

Abstract

The structural analysis is the very basic tool for understanding the properties of a network. In this paper we present a (customizable) tool, able to compute in real-time the most important connectivity properties of a network, modeled as an undirected graph: connected and biconnected components, articulation points and bridges. The algorithm underlying the tool has been theoretically analyzed in the (semi-)streaming model, and has been tested with graphs up to hundreds of millions nodes and billions edges. The tool, therefore, can be employed to monitor traffic flows in medium and large networks, at real-time, and detect possible anomalies. As an application, we provide results about the structural properties of ten years of samples of the Autonomous System network, obtained from the Univ. of Oregon Route Views project, that (once again) shows the ubiquitous presence of power-law distribution.
2011
978-1-4244-9539-9
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14086/382
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