Vincenzo Fioriti

Stability of a Distributed Generation Network Using the Kuramoto Models

We derive a Kuramoto-like equation from the Cardell-Ilic distributed electrical generation network and use the resulting model to simulate the phase stability and the synchronization of a small electrical grid. It is well-known that a major problem for distributed generation is the frequency stability. This is a non linear problem and proper models for analysis are sorely lacking. In our model nodes are arranged in a regular lattice; the strength of their couplings are randomly chosen and allowed to vary as square waves. Although the system undergoes several synchronization losses, nevertheless it is able to quickly resynchronize. Moreover, we show that the synchronization rising-time follows a power-law.

Methodologies for inter-dependency assessment

We report on an recent European Project aimed at assessment of suited Methodologies to measure interdependencies between the Electric and the ICT System. Based on best practices and available data, several different metrics have been defined. Depending on the methodology involved, three main types of metrics can be identified; namely “topological”; “system theory based” and “simulation based” metrics. The selected methodologies have been applied to the Roma Area electric and communication system. Results from all the different approaches are discussed. All metrics provide quantitative measures of the inter-dependence between both the two systems and their components. In addition to the established metrics, a novel “spectral” metric has been introduced specific for cascade effects. Such an innovative methodology has also been applied to the US Power Grid and results compared with those from the Roma Area.

Topological protection from the next generation malware: a survey

The spreading of dangerous malware in inter-dependent networks of electronics devices has raised deep concern, because from the ICT networks infections may propagate to other critical infrastructures producing the well-known domino effect. Researchers are attempting to develop a high level analysis of malware propagation, discarding software details, in order to generalise to the maximum extent the defensive strategies. It has been suggested that the maximum eigenvalue could act as a threshold for the malware spreading. This paper presents a new proof of this statement and an original way to classify the max eigenvalue minimisation problem (NP-hard). A study of the Italian internet autonomous system verifying the theoretical threshold is shown. Finally, it shows how to stop a worm in a real LAN using a new sub-optimal algorithm. Such algorithm suggests which nodes to protect for limiting the worm diffusion according to the spectral paradigm.

Spectral analysis of a real power network

We present a spectral analysis of a significant part of the Italian bulk power system. Spectral analysis applied to graphs is not a new tool, but analyses of the real world, especially of technological networks, currently are lacking. We show the spectral pattern of a high voltage power network, calculate the ratio between the smallest and largest non-zero Laplacian eigenvalue to check its synchronisability and calculate the epidemics threshold of a real HV power grid. We indicate the trade-off between sinchronisability and epidemic threshold as a major network design problem. Moreover, following Restrepo, Ott, Hunt, we propose the usage of the maximum eigenvalue of the adjacency matrix to assess a metric for the inter-dependency in the technological networks.

Identifying sparse and dense sub-graphs in large graphs with a fast algorithm

Identifying the nodes of small sub-graphs with no a priori information is a hard problem. In this work, we want to find each node of a sparse sub-graph embedded in both dynamic and static background graphs, of larger average degree. We show that exploiting the summability over several background realizations of the Estrada-Benzi communicability and the Krylov approximation of the matrix exponential, it is possible to recover the sub-graph with a fast algorithm with computational complexity O(N n). Relaxing the problem to complete sub-graphs, the same performance is obtained with a single background. The worst case complexity for the single background is O(n log(n)).

Sub-optimal Topological Protection Strategy from Advanced Malware

The spreading of dangerous malware in inter-dependent networks of electronics devices has raised deep concern, because from the ICT networks infections may propagate to other Critical Infrastructures producing the well-known domino effect. Researchers are attempting to develop a high level analysis of malware propagation, discarding software details, in order to generalize to the maximum extent the defensive strategies. It has been suggested that the maximum eigenvalue could act as a threshold for the malware’s spreading. In this paper we study the Italian Internet Autonomous System simulating the diffusion of a worm, verifying the theoretical threshold and showing how to choose in a sub-optimal way the set of most influential nodes to protect with respect to the spectral paradigm. Our algorithm is fast and outperforms measures as degree, closeness, betweenness, and dynamical importance.

Mutual validation between different modal analysis techniques for dynamic identification of the so-called Temple of Minerva Medica, Rome

The dynamic identification by ambient vibration data is widely used to supply information on the global health of structures through the investigation of changes in their modal parameters. It can be used even for verification of the state of damage of structures after hazardous threats, for example seismic activity. Therefore, it can play a crucial role to integrate and support conservation strategies for historic architectural assets. Sometimes, in historic constructions only a limited number of positions are accessible or usable to install sensors, and so modal analysis must be based on data from few measurement points. Moreover, they might not be the optimal positions for the studied structure, so the obtained results would need further verification. In such circumstances, the mutual validation between different modal analysis techniques can be useful to assess the reliability of results. In the present paper a case study of application to the so-called Temple of Minerva Medica, Rome, is described. Ambient vibration data were acquired in four rowing acquisition sessions carried out from July 2016 to July 2017, which is a timespan usable to assess the impact of the recent Central Italy seismic sequence. For problems related to the installation of the scaffolding only few points were available for instruments positioning. A variety of techniques were applied, including FRF, FDD, EFDD, SSI, HVSR and complex modal models. The variance of the modal parameters obtained by each different technique was utilized to provide indications on the reliability of the average values.

Motion Magnification for Urban Buildings.

Vibration monitoring of buildings in the urban environment is a relevant issue for health survey and early damaging detection in sustainable and enhanced resilient cities. To this end, we explore the potentialities of vibration monitoring by motion magnification analysis that acts like a microscope for motion in video sequences, but affecting only some groups of pixels. The magnified motion is a new discipline in the field of the analysis of mechanical structures and buildings. It was developed from the analysis of small motions in videos. The motion magnification uses the spatial resolution of the video camera to extract physical properties from images to make inferences about the dynamical behavior of the observed object. The methodology does not rely on optics, but on algorithms capable to amplify only the tiny changes in the video frames, while the large ones remain. Recently, a number of experiments conducted on simple geometries like rods and other small objects, as well as on bridges, showed the reliability of this methodology compared to accelerometers and laser vibrometers. The extension of magnified motion to monitoring of buildings would provide many advantages: a clear, simple, immediate and intuitive diagnosis of the structure, flexibility, predictive potentialities, ease of use, low costs. But also some difficulties still do exist and are discussed. Here we give an introduction to the methodology and some case-studies, both in laboratory and in the real-world (see videos from the link): applications to the short-term urban resilience is straightforward.

Expanding the Time Horizon in Underwater Robot Swarms

In this paper we study the time delays affecting the diffusion of information in an underwater heterogeneous robot swarm in a time-sensitive environment. In many situations each member of the swarm must update its knowledge about the environment as soon as possible, thus every effort to expand the time horizon is useful. Otherwise critical information may not reach nodes far from the source causing dangerous misbehaviour of the swarm. We consider two extreme situations. In the first scenario we have an unique probabilistic delay distribution. In the second scenario, each agent is subject to a different truncated gaussian distribution, meaning local conditions are significantly different from link to link. We study how several swarm topologies react to the two scenarios and how to allocate the more efficient transmission resources in order to expand the time horizon. Results show that significant time savings under a gossip-like protocol are possible properly allocating the resources. Moreover, methods to determine the fastest swarm topologies and the most important nodes are suggested.