Robustness of circularly interdependent networks

作者全名:"Zheng, Kexian; Liu, Ying; Gong, Jie; Wang, Wei"

作者地址:"[Zheng, Kexian; Liu, Ying; Gong, Jie] Southwest Petr Univ, Sch Comp Sci, Chengdu 610500, Peoples R China; [Wang, Wei] Chongqing Med Univ, Sch Publ Hlth & Management, 400016, Chongqing 400016, Peoples R China"

通信作者:"Liu, Y (通讯作者),Southwest Petr Univ, Sch Comp Sci, Chengdu 610500, Peoples R China.; Wang, W (通讯作者),Chongqing Med Univ, Sch Publ Hlth & Management, 400016, Chongqing 400016, Peoples R China."

来源:CHAOS SOLITONS & FRACTALS

ESI学科分类:PHYSICS

WOS号:WOS:000782157700013

JCR分区:Q1

影响因子:7.8

年份:2022

卷号:157

期号: 

开始页: 

结束页: 

文献类型:Article

关键词:Circularly interdependent networks; Robustness; Percolation method

摘要:"Circularly interdependent multilayer networks widely exist in nature, such as the food webs and world trade networks, where each layer depends on one another and the dependencies among all layers form a directed loop. In this paper we study the robustness of the circularly interdependent multilayer networks with three or more layers under random node attacks by using the percolation method. We propose an analytical framework to predict the critical threshold and size of giant component in the steady state, where the analytical results agree well with the simulation results. We focus on two types of depen-dencies, the one-to-one and one-to-many dependency. In the one-to-one interdependent networks, there exists a tricritical point of the node dependence strength at which the phase transition switches between first and second order, which is independent of the average degree and the number of layers. When the dependence strength between node pairs is large, increasing the number of layers leads to the increase of percolation threshold. In the three-layer one-to-many interdependent networks with strong coupling strength, under different inter-layer average degrees, the system undergoes the first-order transition and the robustness of the system increases with the inter-layer average degrees. Our work provides a quanti-tative understanding of the robustness of circularly interdependent networks.(c) 2022 Elsevier Ltd. All rights reserved."

基金机构:"National Natural Science Foun-dation of China [61802321, 61903266]; Sichuan Sci-ence and Technology Program [2020YJ0125, 2020YJ0048]; China Postdoctoral Science Foundation [2019T120829]; Southwest Petroleum University Scientific Research Starting Pro-gram [2019QHZ016]"

基金资助正文:"Acknowledgments This work is supported by the National Natural Science Foun-dation of China (Nos. 61802321 and 61903266) , Sichuan Sci-ence and Technology Program (Nos. 2020YJ0125 and 2020YJ0048) , China Postdoctoral Science Foundation (No. 2019T120829) , and the Southwest Petroleum University Scientific Research Starting Pro-gram (No. 2019QHZ016) ."