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Abstract
It is essential to study the robustness and centrality of interdependent networks for building reliable interdependent systems. Here, we consider a nonlinear load-capacity cascading failure model on interdependent networks, where the initial load distribution is not random, as usually assumed, but determined by the influence of each node in the interdependent network. The node influence is measured by an automated entropy-weighted multi-attribute algorithm that takes into account both different centrality measures of nodes and the interdependence of node pairs, then averaging for not only the node itself but also its nearest neighbors and next-nearest neighbors. The resilience of interdependent networks under such a more practical and accurate setting is thoroughly investigated for various network parameters, as well as how nodes from different layers are coupled and the corresponding coupling strength. The results thereby can help better monitoring interdependent systems.
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Details
1 Hunan University of Science and Technology, School of Information and Electrical Engineering, Xiangtan, People’s Republic of China (GRID:grid.411429.b) (ISNI:0000 0004 1760 6172); Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Shenzhen, People’s Republic of China (GRID:grid.9227.e) (ISNI:0000000119573309)
2 Hunan University of Science and Technology, School of Information and Electrical Engineering, Xiangtan, People’s Republic of China (GRID:grid.411429.b) (ISNI:0000 0004 1760 6172)
3 Northeastern University, Network Science Institute and Department of Physics, Boston, USA (GRID:grid.261112.7) (ISNI:0000 0001 2173 3359)
4 Rensselaer Polytechnic Institute, Department of Computer Science and Network Science and Technology Center, Troy, USA (GRID:grid.33647.35) (ISNI:0000 0001 2160 9198)