Critical node detection problem for complex network in undirected weighted networks

Chen, Wei; Jiang, Manrui; Jiang, Cheng; Zhang, Jun

doi:10.1016/j.physa.2019.122862

Cited by 15 publications

(4 citation statements)

References 45 publications

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“…Existing modeling methods for cascading failures of CPPSs in the literature can be divided into two categories, including, complex network-based and approximate dynamic behavior-based models. The former is characterized by high efficiency and few input parameters, such as betweenness-based model (Chen et al, 2014), dynamical redistribution model (Crucitti et al, 2004), and Medium and Low voltage model (Pagani and Aiello, 2013). However, this category of models contains a large number of unrealistic assumptions and approximations about power flows.…”

Section: Modeling Methods For Cascading Failures Of Cppssmentioning

confidence: 99%

“…In their method, the comprehensive importance of nodes is calculated by the weighted sum of these three measures, and the weights of them are determined through the proposed algorithm that integrates entropy weighting method and the Vlsekriterijumska Optimizacija I Kompromisno Resenje method. Chen et al (2020) modeled the CNI problem as a nonconvex mixed-integer quadratic programming problem. Their method aims to obtain a set of critical nodes that can simultaneously maximize the weights between the nodes and minimize pairwise connectivity.…”

Section: Cpps Resilience Optimization Through Identifying and Protecting Critical Nodesmentioning

confidence: 99%

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Cyber—Physical Power System (CPPS): A review on measures and optimization methods of system resilience

2021

Front. Eng. Manag.

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The Cyber-Physical Power System (CPPS) is one of the most critical infrastructure systems in a country because a stable and secure power supply is a key foundation for national and social development. In recent years, resilience has become a major topic in preventing and mitigating the risks caused by large-scale blackouts of CPPSs. Accordingly, the concept and significance of CPPS resilience are at first explained from the engineering perspective in this study. Then, a review of representative quantitative assessment measures of CPPS resilience applied in the existing literature is provided. On the basis of these assessment measures, the optimization methods of CPPS resilience are reviewed from three perspectives, which are mainly focused on the current research, namely, optimizing the recovery sequence of components, identifying and protecting critical nodes, and enhancing the coupling patterns between physical and cyber networks. The recent advances in modeling methods for cascading failures within the CPPS, which is the theoretical foundation for the resilience assessment and optimization research of CPPSs, are also presented. Lastly, the challenges and future research directions for resilience optimizing of CPPSs are discussed.

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Section: Modeling Methods For Cascading Failures Of Cppssmentioning

confidence: 99%

Section: Cpps Resilience Optimization Through Identifying and Protecting Critical Nodesmentioning

confidence: 99%

Cyber—Physical Power System (CPPS): A review on measures and optimization methods of system resilience

2021

Front. Eng. Manag.

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“…ese studies show that the critical exponent is not universal in some scale-free complex networks. erefore, finding the critical point of complex networks has become an issue of great academic interest, and many algorithms for this purpose have emerged [24,25].…”

Section: Introductionmentioning

confidence: 99%

E-Commerce Credit Network Control Strategy from a Critical Perspective

Zhang

Zheng

2022

Mathematical Problems in Engineering

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Credit problems are the main bottleneck in the development of e-commerce. Both the time and degree of e-commerce credit control directly affect its economic benefits. From the perspective of the criticality of complex systems, this paper explores the control node of e-commerce credit behaviour. Implementing control in this node can not only ensure the stable development of the credit network but also optimise the control cost. This paper constructs a credit behaviour model for the four regulatory behaviours of the transaction subject, analyses the evolution law of the credit network, and determines the critical state of the network. Finally, the paper’s empirical analysis and simulation experiments prove that when the false information in the credit network in the empirical data is 32%, the implementation of credit control has an efficient control effect. Nevertheless, 32% is not a universal result; the specific critical point value needs to be recalculated according to the theoretical derivation of the critical point combined with the actual network. These research results can help regulators obtain the highest regulatory return with the lowest regulatory investment.

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“…e research of the information propagation such as spreading of rumors, influence diffusion, packet forwarding, and epidemic proportions has a long tradition in network science including social network analysis, Internet topology analysis, and complex biological network analysis. Identifying the influential source nodes that make the information propagates as quickly as possible is one of the most important problems in network science, and many researchers did hard works on finding such influential nodes [6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

ITDPM: An Internet Topology Dynamic Propagation Model Based on Generative Adversarial Learning

Zhai

Fei

et al. 2021

Scientific Programming

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Network information propagation analysis is gaining a more important role in network vulnerability analysis domain for preventing potential risks and threats. Identifying the influential source nodes is one of the most important problems to analyze information propagation. Traditional methods mainly focus on extracting nodes that have high degrees or local clustering coefficients. However, these nodes are not necessarily the high influential nodes in many real-world complex networks. Therefore, we propose a novel method for detecting high influential nodes based on Internet Topology Dynamic Propagation Model (ITDPM). The model consists of two processing stages: the generator and the discriminator like the generative adversarial networks (GANs). The generator stage generates the optimal source-driven nodes based on the improved network control theory and node importance characteristics, while the discriminator stage trains the information propagation process and feeds back the outputs to the generator for performing iterative optimization. Based on the generative adversarial learning, the optimal source-driven nodes are then updated in each step via network information dynamic propagation. We apply our method to random-generated complex network data and real network data; the experimental results show that our model has notable performance on identifying the most influential nodes during network operation.

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Critical node detection problem for complex network in undirected weighted networks

Cited by 15 publications

References 45 publications

Cyber—Physical Power System (CPPS): A review on measures and optimization methods of system resilience

Cyber—Physical Power System (CPPS): A review on measures and optimization methods of system resilience

E-Commerce Credit Network Control Strategy from a Critical Perspective

ITDPM: An Internet Topology Dynamic Propagation Model Based on Generative Adversarial Learning

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