602 research outputs found

    Network disruption and recovery: Co-evolution of defender and attacker in a dynamic game

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    The evolution of interactions between individuals or organizations are a central theme of complexity research. We aim at modeling a dynamic game on a network where an attacker and a defender compete in disrupting and reconnecting a network. The choices of how to attack and defend the network are governed by a Genetic Algorithm (GA) which is used to dynamically choose among a set of available strategies. Our analysis shows that the choice of strategy is particularly important if the resources available to the defender are slightly higher than the attackers'. The best strategies found through GAs by the attackers and defenders are based on betweenness centrality. Our results agree with previous literature assessing strategies for network attack and defense in a static context. However, our paper is one of the first ones to show how a GA approach can be applied in a dynamic game on a network. This research provides a starting-point to further explore strategies as we currently apply a limited set of strategies only

    Assortativity Effects on Diffusion-like Processes in Scale-free Networks

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    We study the variation in epidemic thresholds in complex networks with different assortativity properties. We determine the thresholds by applying spectral analysis to the matrices associated to the graphs. In order to produce graphs with a specific assortativity we introduce a procedure to sample the space of all the possible networks with a given degree sequence. Our analysis shows that while disassortative networks have an higher epidemiological threshold, assortative networks have a slower diffusion time for diseases. We also used these networks for evaluating the effects of assortativity in a specific dynamic model of sandpile. We show that immunization procedures give different results according to the assortativity of the network considered

    Phase transitions in Pareto optimal complex networks

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    The organization of interactions in complex systems can be described by networks connecting different units. These graphs are useful representations of the local and global complexity of the underlying systems. The origin of their topological structure can be diverse, resulting from different mechanisms including multiplicative processes and optimization. In spatial networks or in graphs where cost constraints are at work, as it occurs in a plethora of situations from power grids to the wiring of neurons in the brain, optimization plays an important part in shaping their organization. In this paper we study network designs resulting from a Pareto optimization process, where different simultaneous constraints are the targets of selection. We analyze three variations on a problem finding phase transitions of different kinds. Distinct phases are associated to different arrangements of the connections; but the need of drastic topological changes does not determine the presence, nor the nature of the phase transitions encountered. Instead, the functions under optimization do play a determinant role. This reinforces the view that phase transitions do not arise from intrinsic properties of a system alone, but from the interplay of that system with its external constraints.Comment: 14 pages, 7 figure

    Situated Technologies

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    Architecture's privileged position as the technology of space-making is challenged by the current proliferation of a wide range of mobile, embedded, networked and distributed media, communication and information systems. Our interactions with (and through) these location-based, context-aware and otherwise ”situated” technologies are beginning to alter the way we perceive, navigate and socialize within the built environment. Prompting a reconfiguration of material boundaries, organizational adjacencies, and public/private relations, these technologies (and the ways in which we engage them) have significant implications for how we conceive, design and experience space. In this paper, we identify three vectors for architectural research that explore the spatial opportunities presented by what we call Situated Technologies. Working across the overlapping boundaries of media, architecture and computing, this research attempts to articulate how architects might play a critical role in shaping evolving techno-social spaces increasingly governed by both material and immaterial processes. As exploratory research, it aims less to propose solutions to known problems than to arrive at precise questions that help us better identify and structure new problems for architecture presented by recent developments in ubiquitous/ pervasive computing

    Topological street-network characterization through feature-vector and cluster analysis

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    Complex networks provide a means to describe cities through their street mesh, expressing characteristics that refer to the structure and organization of an urban zone. Although other studies have used complex networks to model street meshes, we observed a lack of methods to characterize the relationship between cities by using their topological features. Accordingly, this paper aims to describe interactions between cities by using vectors of topological features extracted from their street meshes represented as complex networks. The methodology of this study is based on the use of digital maps. Over the computational representation of such maps, we extract global complex-network features that embody the characteristics of the cities. These vectors allow for the use of multidimensional projection and clustering techniques, enabling a similarity-based comparison of the street meshes. We experiment with 645 cities from the Brazilian state of Sao Paulo. Our results show how the joint of global features describes urban indicators that are deep-rooted in the network's topology and how they reveal characteristics and similarities among sets of cities that are separated from each other.Comment: Paper to be published on the International Conference on Computational Science (ICCS), 201

    Towards the Internet of Smart Trains: A Review on Industrial IoT-Connected Railways

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    [Abstract] Nowadays, the railway industry is in a position where it is able to exploit the opportunities created by the IIoT (Industrial Internet of Things) and enabling communication technologies under the paradigm of Internet of Trains. This review details the evolution of communication technologies since the deployment of GSM-R, describing the main alternatives and how railway requirements, specifications and recommendations have evolved over time. The advantages of the latest generation of broadband communication systems (e.g., LTE, 5G, IEEE 802.11ad) and the emergence of Wireless Sensor Networks (WSNs) for the railway environment are also explained together with the strategic roadmap to ensure a smooth migration from GSM-R. Furthermore, this survey focuses on providing a holistic approach, identifying scenarios and architectures where railways could leverage better commercial IIoT capabilities. After reviewing the main industrial developments, short and medium-term IIoT-enabled services for smart railways are evaluated. Then, it is analyzed the latest research on predictive maintenance, smart infrastructure, advanced monitoring of assets, video surveillance systems, railway operations, Passenger and Freight Information Systems (PIS/FIS), train control systems, safety assurance, signaling systems, cyber security and energy efficiency. Overall, it can be stated that the aim of this article is to provide a detailed examination of the state-of-the-art of different technologies and services that will revolutionize the railway industry and will allow for confronting today challenges.Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED431C 2016-045Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED341D R2016/012Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED431G/01Agencia Estatal de Investigación (España); TEC2013-47141-C4-1-RAgencia Estatal de Investigación (España); TEC2015-69648-REDCAgencia Estatal de Investigación (España); TEC2016-75067-C4-1-

    The structure and function of complex networks

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    Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.Comment: Review article, 58 pages, 16 figures, 3 tables, 429 references, published in SIAM Review (2003

    Graph-theoretical consideration in the design of complex engineering systems for robustness and scalability

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    Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2005.Includes bibliographical references (p. 113-114).(cont.) and (2) a forward approach which achieves optimality at the start and grows the system using an optimization technique. We systematically compare the two staging techniques in the context of telescope arrays and evaluate the hypothesis that the backward approach is superior for telescope arrays because it incorporates knowledge of the desired future end state of the system. The modelling framework introduced is applicable to various engineering problems susceptible to network representation, including biological systems, telecommunication networks, transportation routes, and space exploration systems.System optimization for extensibility and robustness is a fundamental challenge of engineering disciplines. Traditional approaches have aimed to optimize cost and performance of a system at a given point in its lifespan. However, as systems evolve with increasing resources and load, system extensibility has to be included in the earliest stages of planning and deployment. In this thesis, we study the staged deployment of large telescope array configurations as an optimization problem subject to cost, performance and network robustness. The LOFAR (LOw Frequency ARray) is the world's largest telescope array, deploying in its full design 25000 antennas over 350kin in diameter in Northern Europe. These are deployed in clusters, and planned to be built in stages, with current funding allowing for 15000 arrays over 100km. This new generation of telescope arrays requires new system design principles and modelling techniques. We develop a staged optimization framework for modelling network behavior, robustness, and extensibility. We represent large telescope arrays as generalized networks, with nodes as the telescope stations and edges as the cable links between them. We model network design and growth with both graph-theoretical and physical metrics pertaining to imaging properties of each array configuration. Additionally, we model the probability of failure of each topology, both from environmental conditions and random events along the baseline. We make recommendations about the best cost-performance and robustness trade-off configurations. We introduce two staging principles for system deployment and configuration: (1) a backward approach, in which the design is optimized in the future and scaled down for the initial stages,by Gergana Assenova Bounova.S.M
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