The robustness of sparse network under limited attack capacity
The paper studies the robustness of the network in terms of the network structure. We define a strongly dominated relation between nodes and then we use the relation to merge the network. Based on that, we design a dominated clustering algorithm aiming at finding the critical nodes in the network. F...
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| Published in | Chinese physics B Vol. 26; no. 8; pp. 577 - 586 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
01.08.2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1674-1056 2058-3834 |
| DOI | 10.1088/1674-1056/26/8/088901 |
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| Summary: | The paper studies the robustness of the network in terms of the network structure. We define a strongly dominated relation between nodes and then we use the relation to merge the network. Based on that, we design a dominated clustering algorithm aiming at finding the critical nodes in the network. Furthermore, this merging process is lossless which means the original structure of the network is kept. In order to realize the visulization of the network, we also apply the lossy consolidation to the network based on detection of the community structures. Simulation results show that compared with six existed centrality algorithms, our algorithm performs better when the attack capacity is limited. The simulations also illustrate our algorithm does better in assortative scale-free networks. |
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| Bibliography: | robustness, dominated relation, merge, lossless The paper studies the robustness of the network in terms of the network structure. We define a strongly dominated relation between nodes and then we use the relation to merge the network. Based on that, we design a dominated clustering algorithm aiming at finding the critical nodes in the network. Furthermore, this merging process is lossless which means the original structure of the network is kept. In order to realize the visulization of the network, we also apply the lossy consolidation to the network based on detection of the community structures. Simulation results show that compared with six existed centrality algorithms, our algorithm performs better when the attack capacity is limited. The simulations also illustrate our algorithm does better in assortative scale-free networks. 11-5639/O4 Xiao-Juan Wang1, Mei Song1, Lei Jin1, and Zhen Wang2（ 1Electronic Engineering Institute, Beijing University of Posts and Telecommunications, Beijing 100876, China 2Electronic Engineering Institute of PLA, Hefei 230000, China） |
| ISSN: | 1674-1056 2058-3834 |
| DOI: | 10.1088/1674-1056/26/8/088901 |