scholarly journals Dynamical analysis and control strategies of an SIVS epidemic model with imperfect vaccination on scale-free networks

2019 ◽  
Vol 99 (2) ◽  
pp. 1507-1523 ◽  
Author(s):  
Wei Lv ◽  
Qing Ke ◽  
Kezan Li
Keyword(s):  
Epidemic Model ◽  
Control Strategies ◽  
Dynamical Analysis ◽  
Scale Free ◽  
Scale Free Networks ◽  
And Control

Dynamics of an epidemic model with quarantine on scale-free networks

2017 ◽  
Vol 381 (47) ◽  
pp. 3945-3951 ◽  
Author(s):  
Huiyan Kang ◽  
Kaihui Liu ◽  
Xinchu Fu
Keyword(s):  
Epidemic Model ◽  
Scale Free ◽  
Scale Free Networks

scholarly journals Controllability and Optimization of Complex Networks Based on Bridges

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Lifu Wang ◽  
Guotao Zhao ◽  
Zhi Kong ◽  
Yunkang Zhao
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Betweenness Centrality ◽  
The Other ◽  
Connected Components ◽  
Scale Free ◽  
Scale Free Networks ◽  
Model Networks ◽  
Simulation Results ◽  
And Control

In a complex network, each edge has different functions on controllability of the whole network. A network may be out of control due to failure or attack of some specific edges. Bridges are a kind of key edges whose removal will disconnect a network and increase connected components. Here, we investigate the effects of removing bridges on controllability of network. Various strategies, including random deletion of edges, deletion based on betweenness centrality, and deletion based on degree of source or target nodes, are used to compare with the effect of removing bridges. It is found that the removing bridges strategy is more efficient on reducing controllability than the other strategies of removing edges for ER networks and scale-free networks. In addition, we also found the controllability robustness under edge attack is related to the average degree of complex networks. Therefore, we propose two optimization strategies based on bridges to improve the controllability robustness of complex networks against attacks. The effectiveness of the proposed strategies is demonstrated by simulation results of some model networks. These results are helpful for people to understand and control spreading processes of epidemic across different paths.

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