Robustness of weighted networks with the harmonic closeness against cascading failures

Hao, Yucheng; Jia, Limin; Wang, Yanhui

doi:10.1016/j.physa.2019.123373

Cited by 17 publications

(9 citation statements)

References 37 publications

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“…Subsequently, many scholars have studied the robustness of different complex network structures (e.g., regular networks, random networks, small-world networks, and scale-free networks). Research content includes network structure, model parameters, degradation mode, robust decision making, and other aspects [ 41 , 42 ]. With the wide application of OSD in various industries, researchers are devoting increasing attention to the robustness and stability of OSC networks.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Robustness of Open-Source Project Knowledge Collaborative Network Based on Opinion Leader Identification

Lei

Zhang

Liu

2021

Entropy

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A large amount of semantic content is generated during designer collaboration in open-source projects (OSPs). Based on the characteristics of knowledge collaboration behavior in OSPs, we constructed a directed, weighted, semantic-based knowledge collaborative network. Four social network analysis indexes were created to identify the key opinion leader nodes in the network using the entropy weight and TOPSIS method. Further, three degradation modes were designed for (1) the collaborative behavior of opinion leaders, (2) main knowledge dissemination behavior, and (3) main knowledge contribution behavior. Regarding the degradation model of the collaborative behavior of opinion leaders, we considered the propagation characteristics of opinion leaders to other nodes, and we created a susceptible–infected–removed (SIR) propagation model of the influence of opinion leaders’ behaviors. Finally, based on empirical data from the Local Motors open-source vehicle design community, a dynamic robustness analysis experiment was carried out. The results showed that the robustness of our constructed network varied for different degradation modes: the degradation of the opinion leaders’ collaborative behavior had the lowest robustness; this was followed by the main knowledge dissemination behavior and the main knowledge contribution behavior; the degradation of random behavior had the highest robustness. Our method revealed the influence of the degradation of collaborative behavior of different types of nodes on the robustness of the network. This could be used to formulate the management strategy of the open-source design community, thus promoting the stable development of OSPs.

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Section: Related Workmentioning

confidence: 99%

Dynamic Robustness of Open-Source Project Knowledge Collaborative Network Based on Opinion Leader Identification

Lei

Zhang

Liu

2021

Entropy

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“…Recently, works [ 42 , 43 ] investigate the cascading models where the loads on nodes and edges are decided by the harmonic closeness which is defined as follows, where hc i represents the harmonic closeness of node i . N is the number of nodes and d ij represents the shortest distance between node i and node j .…”

Section: Modelmentioning

confidence: 99%

Modelling cascading failures in networks with the harmonic closeness

et al. 2021

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Many studies on cascading failures adopt the degree or the betweenness of a node to define its load. From a novel perspective, we propose an approach to obtain initial loads considering the harmonic closeness and the impact of neighboring nodes. Based on simulation results for different adjustable parameter θ, local parameter δ and proportion of attacked nodes f, it is found that in scale-free networks (SF networks), small-world networks (SW networks) and Erdos-Renyi networks (ER networks), there exists a negative correlation between optimal θ and δ. By the removal of the low load node, cascading failures are more likely to occur in some cases. In addition, we find a valuable result that our method yields better performance compared with other methods in SF networks with an arbitrary f, SW and ER networks with large f. Moreover, the method concerning the harmonic closeness makes these three model networks more robust for different average degrees. Finally, we perform the simulations on twenty real networks, whose results verify that our method is also effective to distribute the initial load in different real networks.

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“…As a result of the impact of cascading failures, Motter et al developed a cascading model where the load on the node is dependent on the total number of shortest paths passing through it [13,14]. Additionally, the degree [15,16], the betweenness [17], and the harmonic closeness [18,19], as metrics of nodes to quantify their characteristics, have been widely adopted to obtain the load. Similarly, in order to define the cascading failure model concerning the edge, these measures have also been further studied [20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, in order to define the cascading failure model concerning the edge, these measures have also been further studied [20][21][22][23][24]. On the basis of the comparison of different definitions of the load, Hao et al found that the networks where the loads on the node and edge are defined as the harmonic closeness have a higher level of robustness [18,19,24]. Different from the cascading failure induced by overloads, Newman et al employed the generating function formalism to study the failure process of nodes and edges by means of percolation theory from another perspective [25].…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Analysis of Robustness in Interdependent Mechatronic Systems under Attack Strategies

Wang

Hao

et al. 2021

Discrete Dynamics in Nature and Society

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With the development of mechatronic systems, different kinds of subsystems within them are highly correlated to each other due to the demand for the special function. To assess the robustness in the mechatronic system under various disturbances, we build an interdependent mechatronic system as an interdependent machine-electricity-communication network (IMECN) and adopt the improved cascading failure model where the occurrence of the failure propagation is decided by a proportion threshold δ. In order to fully explore the robustness under different disturbances, we develop attack strategies concerning nodes, edges, and interdependent links by considering measures for a node. Then, we also define the robustness metric to quantify the performance of IMECN during the entire attack process. The mass transit vehicle is taken as an example to investigate the impact of attack strategies on the robustness at different δ in a real-world mechatronic system. It is found that each subnetwork in this IMECN has a scale-free property. Based on simulation results, we obtain the most efficient attack strategies to remove nodes, edges, and interdependent links for different possibilities of triggering the failure propagation. In addition, we find that the attacks on nodes and interdependent links make IMECN more vulnerable compared with the ones on edges. This work provides theoretical insights into the comprehensive analysis of the robustness in interdependent mechatronic systems.

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Robustness of weighted networks with the harmonic closeness against cascading failures

Cited by 17 publications

References 37 publications

Dynamic Robustness of Open-Source Project Knowledge Collaborative Network Based on Opinion Leader Identification

Dynamic Robustness of Open-Source Project Knowledge Collaborative Network Based on Opinion Leader Identification

Modelling cascading failures in networks with the harmonic closeness

A Comprehensive Analysis of Robustness in Interdependent Mechatronic Systems under Attack Strategies

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