84,770 research outputs found
Network hierarchy evolution and system vulnerability in power grids
(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.The seldom addressed network hierarchy property and its relationship with vulnerability analysis for power transmission grids from a complex-systems point of view are given in this paper. We analyze and compare the evolution of network hierarchy for the dynamic vulnerability evaluation of four different power transmission grids of real cases. Several meaningful results suggest that the vulnerability of power grids can be assessed by means of a network hierarchy evolution analysis. First, the network hierarchy evolution may be used as a novel measurement to quantify the robustness of power grids. Second, an antipyramidal structure appears in the most robust network when quantifying cascading failures by the proposed hierarchy metric. Furthermore, the analysis results are also validated and proved by empirical reliability data. We show that our proposed hierarchy evolution analysis methodology could be used to assess the vulnerability of power grids or even other networks from a complex-systems point of view.Peer ReviewedPostprint (author's final draft
Immunization of complex networks
Complex networks such as the sexual partnership web or the Internet often
show a high degree of redundancy and heterogeneity in their connectivity
properties. This peculiar connectivity provides an ideal environment for the
spreading of infective agents. Here we show that the random uniform
immunization of individuals does not lead to the eradication of infections in
all complex networks. Namely, networks with scale-free properties do not
acquire global immunity from major epidemic outbreaks even in the presence of
unrealistically high densities of randomly immunized individuals. The absence
of any critical immunization threshold is due to the unbounded connectivity
fluctuations of scale-free networks. Successful immunization strategies can be
developed only by taking into account the inhomogeneous connectivity properties
of scale-free networks. In particular, targeted immunization schemes, based on
the nodes' connectivity hierarchy, sharply lower the network's vulnerability to
epidemic attacks
Potentialities of Complex Network Theory Tools for Urban Drainage Networks Analysis
Urban drainage networks (UDNs) represent important infrastructures to protect and maintain community health and safety. For these reasons, technicians and researcher are focusing more and more on topics related to vulnerability, resilience and monitoring for controlling illicit intrusions, contaminant and pathogenic spread. In the last years the complex network theory (CNT) is attracting attention as a new, useful and structured approach to analyze urban systems. The aim of this work is to evaluate potentialities of CNT approaches for UDNs vulnerability assessment and monitoring system planning. Limits and potentialities of applicability of CNT tools to UDNs are first provided evaluating the performances of standard centrality metrics. Then, it is proposed the use of tailored metrics embedding prior information, as intrinsic relevance of each node and pipe flow direction, which derive from the Horton's hierarchy and geometric data (pipe slope), respectively, without performing hydraulic simulations. The analysis is applied on two schematic literature networks of different complexity and to a real case-study. The results suggest that vulnerability/resilience, monitoring design, contaminant and pathogenic spreads can be effectively analyzed using tailored metrics. Therefore, the proposed approach represents a complementary tool respect the more complex and computationally expensive methodologies and it is particular useful for large complex networks
Software systems through complex networks science: Review, analysis and applications
Complex software systems are among most sophisticated human-made systems, yet
only little is known about the actual structure of 'good' software. We here
study different software systems developed in Java from the perspective of
network science. The study reveals that network theory can provide a prominent
set of techniques for the exploratory analysis of large complex software
system. We further identify several applications in software engineering, and
propose different network-based quality indicators that address software
design, efficiency, reusability, vulnerability, controllability and other. We
also highlight various interesting findings, e.g., software systems are highly
vulnerable to processes like bug propagation, however, they are not easily
controllable
What lies beneath? The role of informal and hidden networks in the management of crises
Crisis management research traditionally focuses on the role of formal communication networks in the escalation and management of organisational crises. Here, we consider instead informal and unobservable networks. The paper explores how hidden informal exchanges can impact upon organisational decision-making and performance, particularly around inter-agency working, as knowledge distributed across organisations and shared between organisations is often shared through informal means and not captured effectively through the formal decision-making processes. Early warnings and weak signals about potential risks and crises are therefore often missed. We consider the implications of these dynamics in terms of crisis avoidance and crisis management
Some Properties of the Speciation Model for Food-Web Structure - Mechanisms for Degree Distributions and Intervality
We present a mathematical analysis of the speciation model for food-web
structure, which had in previous work been shown to yield a good description of
empirical data of food-web topology. The degree distributions of the network
are derived. Properties of the speciation model are compared to those of other
models that successfully describe empirical data. It is argued that the
speciation model unifies the underlying ideas of previous theories. In
particular, it offers a mechanistic explanation for the success of the niche
model of Williams and Martinez and the frequent observation of intervality in
empirical food webs.Comment: 23 pages, 6 figures, minor rewrite
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