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      Self-organized network design by link survivals and shortcuts

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          Abstract

          One of the challenges for future infrastructures is how to design a network with high efficiency and strong connectivity at low cost. We propose self-organized geographical networks beyond the vulnerable scale-free structure found in many real systems. The networks with spatially concentrated nodes emerge through link survival and path reinforcement on routing flows in a wireless environment with a constant transmission range of a node. In particular, we show that adding some shortcuts induces both the small-world effect and a significant improvement of the robustness to the same level as in the optimal bimodal networks. Such a simple universal mechanism will open prospective ways for several applications in wide-area ad hoc networks, smart grids, and urban planning.

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          Error and attack tolerance of complex networks

          Many complex systems, such as communication networks, display a surprising degree of robustness: while key components regularly malfunction, local failures rarely lead to the loss of the global information-carrying ability of the network. The stability of these complex systems is often attributed to the redundant wiring of the functional web defined by the systems' components. In this paper we demonstrate that error tolerance is not shared by all redundant systems, but it is displayed only by a class of inhomogeneously wired networks, called scale-free networks. We find that scale-free networks, describing a number of systems, such as the World Wide Web, Internet, social networks or a cell, display an unexpected degree of robustness, the ability of their nodes to communicate being unaffected by even unrealistically high failure rates. However, error tolerance comes at a high price: these networks are extremely vulnerable to attacks, i.e. to the selection and removal of a few nodes that play the most important role in assuring the network's connectivity.
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            The diameter of the world wide web

            , , (1999)
            Despite its increasing role in communication, the world wide web remains the least controlled medium: any individual or institution can create websites with unrestricted number of documents and links. While great efforts are made to map and characterize the Internet's infrastructure, little is known about the topology of the web. Here we take a first step to fill this gap: we use local connectivity measurements to construct a topological model of the world wide web, allowing us to explore and characterize its large scale properties.
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              Modelling the Evolution of Human Trail Systems

              Many human social phenomena, such as cooperation, the growth of settlements, traffic dynamics and pedestrian movement, appear to be accessible to mathematical descriptions that invoke self-organization. Here we develop a model of pedestrian motion to explore the evolution of trails in urban green spaces such as parks. Our aim is to address such questions as what the topological structures of these trail systems are, and whether optimal path systems can be predicted for urban planning. We use an `active walker' model that takes into account pedestrian motion and orientation and the concomitant feedbacks with the surrounding environment. Such models have previously been applied to the study of complex structure formation in physical chemical and biological systems. We find that our model is able to reporduce many of the observed large-scale spatial features of trail systems.
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                Author and article information

                Journal
                2011-08-23
                2011-09-24
                Article
                10.1016/j.physa.2011.08.047
                1108.4729
                4d5825f1-0c74-4615-a518-6d40a95a2338

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                Physica A 391, pp.872-879, 2012
                15 pages, 8 figures, 2 tables
                physics.soc-ph cs.SI

                Social & Information networks,General physics
                Social & Information networks, General physics

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