Controllability and Optimization of Complex Networks Based on Bridges
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 invest...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/6695026 |
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| _version_ | 1832560158302011392 |
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| author | Lifu Wang Guotao Zhao Zhi Kong Yunkang Zhao |
| author_facet | Lifu Wang Guotao Zhao Zhi Kong Yunkang Zhao |
| author_sort | Lifu Wang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-0f9b4b11cd35480bb77ee43b44c32783 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-0f9b4b11cd35480bb77ee43b44c327832025-02-03T01:28:10ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/66950266695026Controllability and Optimization of Complex Networks Based on BridgesLifu Wang0Guotao Zhao1Zhi Kong2Yunkang Zhao3School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, ChinaSchool of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, ChinaSchool of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, ChinaSchool of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, ChinaIn 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.http://dx.doi.org/10.1155/2020/6695026 |
| spellingShingle | Lifu Wang Guotao Zhao Zhi Kong Yunkang Zhao Controllability and Optimization of Complex Networks Based on Bridges Complexity |
| title | Controllability and Optimization of Complex Networks Based on Bridges |
| title_full | Controllability and Optimization of Complex Networks Based on Bridges |
| title_fullStr | Controllability and Optimization of Complex Networks Based on Bridges |
| title_full_unstemmed | Controllability and Optimization of Complex Networks Based on Bridges |
| title_short | Controllability and Optimization of Complex Networks Based on Bridges |
| title_sort | controllability and optimization of complex networks based on bridges |
| url | http://dx.doi.org/10.1155/2020/6695026 |
| work_keys_str_mv | AT lifuwang controllabilityandoptimizationofcomplexnetworksbasedonbridges AT guotaozhao controllabilityandoptimizationofcomplexnetworksbasedonbridges AT zhikong controllabilityandoptimizationofcomplexnetworksbasedonbridges AT yunkangzhao controllabilityandoptimizationofcomplexnetworksbasedonbridges |