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Previous researches on cascading failures on interdependent networks with cliques mainly consider "strong" interdependence, that is, once a clique fails, its dependency partner in the other layer will fail completely. However, man...
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Previous researches on cascading failures on interdependent networks with cliques mainly consider "strong" interdependence, that is, once a clique fails, its dependency partner in the other layer will fail completely. However, many interdependent systems in real-world may have self-sustaining abilities, and the failure of one clique may only destroy part of the function of its dependency partner, which can be called "weak" interdependence. In this paper, based on the framework of percolation, a cascading failure model on the interdependent networks with cliques and weak interdependence is investigated analytically and numerically. The results of extensive simulations show that the type of the phase transitions of both layers can be altered from discontinuous phase transitions to continuous phase transitions with the decrease of interdependence strength. In addition, in the process from discontinuous phase transitions to continuous phase transitions, the whole system exhibits a surprising phenomenon of mixed phase transitions: layer with large size of cliques percolates continuously while layer with small size of cliques percolates discontinuously. It indicates that weak interdependence strength and the structure of cliques can enhance the robustness of the interdependent networks. The theoretical and numerical predictions agree well with each other. (C) 2020 Elsevier B.V. All rights reserved.
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Two stochastic models are proposed to generate a system composed of two interdependent scale-free (SF) or Erd?s–Rényi (ER) networks where interdependent nodes are connected with an exponential or power-law relation, as well as d...
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Two stochastic models are proposed to generate a system composed of two interdependent scale-free (SF) or Erd?s–Rényi (ER) networks where interdependent nodes are connected with an exponential or power-law relation, as well as different dependence strength, respectively. Each subnetwork grows through the addition of new nodes with constant accelerating random attachment in the first model but with preferential attachment in the second model. The two subnetworks interact with multi-support and undirectional dependence links. The effects of dependence relations and strength between subnetworks are analyzed in the percolation behavior of fully interdependent networks against random failure, both theoretically and numerically, and as a result, for both relations: interdependent SF networks show a second-order percolation phase transition and the increased dependence strength decreases the robustness of the system, whereas, interdependent ER networks show the opposite results. In addition, the power-law relation between networks yields greater robustness than the exponential one at the given dependence strength.
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Edge-based interdependent networks (EIN) where edges in one network layer are interdependent with edges in other layers, as contrast to the classical interdependent networks (NIN) where nodes in one layer are interdependent with n...
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Edge-based interdependent networks (EIN) where edges in one network layer are interdependent with edges in other layers, as contrast to the classical interdependent networks (NIN) where nodes in one layer are interdependent with nodes in other layers, have been an emerging topic in the field of interdependent networks. In this paper, by proposing an EIN on a quenched network perspective, we find that EIN is generally more robust than NIN and further reveal that this property roots in the fact that in a network the excessive degree of an edge is on an average larger than the degree of a node. A theory is developed based on a quenched network framework to verify this property, where the notion of compound excessive degree (CED) of an edge is introduced. The introduction of CED allows to define several novel properties of EIN, including the interlayer correlation and malicious attack relevant to CED. Systematic investigations on these properties are provided to extend the understanding of interdependent networks from the perspective of edge-interdependency. (c) 2022 Elsevier Ltd. All rights reserved.
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We consider the problem of optimizing the operations of interdependent infrastructure systems in a resource-constrained environment. In this problem, decisions consist of determining the set of components that will be operational ...
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We consider the problem of optimizing the operations of interdependent infrastructure systems in a resource-constrained environment. In this problem, decisions consist of determining the set of components that will be operational and how services from different infrastructures will be delivered to operational components. We propose an interdependent multi-layered network flow (IMN) model to solve this problem. In this model, interdependent infrastructures are represented by networks and movement of commodities or services by flows. We seek to maximize the reward obtained from operational components minus the cost of routing flows. We show that IMN is NP-hard in the strong sense even in the case of a single-layer network. We further propose families of valid inequalities for the integer programming formulation of IMN, which are then utilized to develop a solution approach for the problem. The solution approach is tested on synthesized data sets of interdependent infrastructure systems. Our computational results demonstrate that our solution approach can obtain high-quality solutions in less computational time when compared to the mixed integer programming (MIP) formulation solved with standard software for most of the instances. We also show the capability of IMN over the previous models in the literature on interdependent infrastructures' operations. (C) 2020 Elsevier Ltd. All rights reserved.
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For critical infrastructure restoration planning, the real-time scheduling and coordination of system restoration efforts, the key in decision-making is to prioritize those critical components that are out of service during the re...
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For critical infrastructure restoration planning, the real-time scheduling and coordination of system restoration efforts, the key in decision-making is to prioritize those critical components that are out of service during the restoration. For this purpose, there is a need for component importance analysis. While it has been investigated extensively for individ-ual systems, component importance considering interdependence among transmission, distribution and communication (T&D&C) systems has not been systematically analyzed and widely adopted. In this study, we propose a component importance assessment method in the context of interdependence between T&D&C networks. Analytic methods for multilayer networks and a set of metrics have been applied for assessing the component impor-tance and interdependence between T&D&C networks based on their physical characteristics. The proposed methodology is further validated with integrated synthetic Illinois regional trans-mission, distribution, and communication (T&D&C) systems, the results reveal the unique characteristics of component/node importance, which may be strongly affected by the network topology and cross-domain node mapping.
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We carry out a study of percolation behaviors of clustered networks with partial support–dependence relations by adopting two different attacking strategies, attacking only one network and both networks, which help to further und...
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We carry out a study of percolation behaviors of clustered networks with partial support–dependence relations by adopting two different attacking strategies, attacking only one network and both networks, which help to further understand real coupled networks. For two different attacking strategies we find that the system changes from a second-order phase transition to a first-order phase transition as coupling strength q increases. We also notice that the first-order region becomes smaller and the secondorder region becomes larger as average degree or clustering coefficient increases. And, as the average supported degree approaches infinity, coupled clustered networks become independent and only the second-order transition is observed, which is similar to q = 0. Furthermore, we find that clustering coefficient has a significant impact on robustness of the system for strong coupling strength, but for weak coupling strength it has little influence, especially for attacking both networks. The study implies that we can obtain a more robust network by reducing clustering coefficient and increasing average degree for strong coupling strength. However, for weak coupling strength, a more robust network is obtained only by increasing average degree for the same support average degree. Additionally,wefind that for attacking both networks the system becomes more vulnerable and difficult to defend compared to attacking only one network.
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For complex systems, the effect of increasing the complexity may either enhance the robustness or aggravate the fragility of the systems. In order to understand the two-fold effect of the complexity, in this paper we use interdepe...
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For complex systems, the effect of increasing the complexity may either enhance the robustness or aggravate the fragility of the systems. In order to understand the two-fold effect of the complexity, in this paper we use interdependent networks to represent the complex systems, and introduce the redundant and dependent connections across different layers (interconnections) to study how the complexity influence the robustness and fragility of the systems. Specifically, we consider the redundant and dependent interconnections from two aspects which are the number of the layers and the number of multiple connections among nodes in different layers. By adopting a message-passing approach, we show that the addition of redundant interlayer connections could enhance the robustness of the systems, and conversely, the fragility of the systems aggravates with additional dependent interlayer connections. Furthermore, we find that the influence from the aspect of the number of multiple connections among nodes are stronger than the aspect from the number of layers. (C) 2019 Elsevier B.V. All rights reserved.
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Compared with a single and isolated network, interdependent networks have two types of links: connectivity link and dependency link. This paper aims to improve the robustness of interdependent networks by adding connectivity links...
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Compared with a single and isolated network, interdependent networks have two types of links: connectivity link and dependency link. This paper aims to improve the robustness of interdependent networks by adding connectivity links. Firstly, interdependent networks failure model and four frequently used link addition strategies are briefly reviewed. Furthermore, by defining inter degree-degree difference, two novel link addition strategies are proposed. Finally, we verify the effectiveness of our proposed link addition strategies by comparing with the current link addition strategies in three different network models. The simulation results show that, given the number of added links, link allocation strategies have great effects on the robustness of interdependent networks, i.e., the double-network link allocation strategy is superior to single-network link allocation strategy. Link addition strategies proposed in this paper excel the current strategies, especially for BA interdependent networks. Moreover, our work can provide guidance on how to allocate limited resources to an existing interdependent networks system and optimize its topology to avoid the potential cascade failures. (C) 2015 Elsevier B.V. All rights reserved.
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Analysis of the interdependencies between interconnected critical infrastructures can help enhance the robustness of the individual infrastructures as well as the overall interconnected infrastructures. One of the most studied int...
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Analysis of the interdependencies between interconnected critical infrastructures can help enhance the robustness of the individual infrastructures as well as the overall interconnected infrastructures. One of the most studied interdependent critical infrastructure network scenarios is a power grid connected to a backbone telecommunications network. In this interdependent infrastructure scenario, the robustness of the entire system is usually analyzed in the context of cascading failure models in the power grid. However, this paper focuses on targeted attacks, where an attack on a telecommunications network node directly affects a connected power grid node, and vice versa. Cascading failures are outside the scope of this paper because the objective is to enhance the robustness of the interconnections between the infrastructures. In order to mitigate the impacts of targeted attacks on the interdependent infrastructures, three interdependency matrices for connecting the infrastructures are specified and analyzed. The analysis identifies the interdependency matrix that best reduces the impacts of targeted attacks and the propagation of failures between the infrastructures. Additionally, the impacts of interconnecting a power grid to different telecommunications networks, each with different susceptibilities to targeted attacks, is evaluated. (C) 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.
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Cascading failures on interdependent networks have attracted much attention in recent years. In this paper, we study a cascading failure model on interdependent networks with multiple dependency relations and cliques, in which a c...
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Cascading failures on interdependent networks have attracted much attention in recent years. In this paper, we study a cascading failure model on interdependent networks with multiple dependency relations and cliques, in which a clique is dependent on multiple cliques in other network and all nodes in the same clique are survive or fail together. Through a percolation theory, we find that the system always undergoes a first order phase transition when the dependency relations are small. The robustness of the system increases with increasing the number of multiple dependency relations between two networks and the size of cliques. The theory can well predict the numerical simulations. (C) 2019 Elsevier B.V. All rights reserved.
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