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Enhancing structural robustness of scale-free networks by information disturbance
Many real-world systems can be described by scale-free networks with power-law degree distributions. Scale-free networks show a “robust yet fragile” feature due to their heterogeneous degree distributions. We propose to enhance the structural robustness of scale-free networks against intentional att...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5548747/ https://www.ncbi.nlm.nih.gov/pubmed/28790416 http://dx.doi.org/10.1038/s41598-017-07878-2 |
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author | Wu, Jun Tan, Suo-Yi Liu, Zhong Tan, Yue-Jin Lu, Xin |
author_facet | Wu, Jun Tan, Suo-Yi Liu, Zhong Tan, Yue-Jin Lu, Xin |
author_sort | Wu, Jun |
collection | PubMed |
description | Many real-world systems can be described by scale-free networks with power-law degree distributions. Scale-free networks show a “robust yet fragile” feature due to their heterogeneous degree distributions. We propose to enhance the structural robustness of scale-free networks against intentional attacks by changing the displayed network structure information rather than modifying the network structure itself. We first introduce a simple mathematical model for attack information and investigate the impact of attack information on the structural robustness of scale-free networks. Both analytical and numerical results show that decreasing slightly the attack information perfection by information disturbance can dramatically enhance the structural robustness of scale-free networks. Then we propose an optimization model of disturbance strategies in which the cost constraint is considered. We analyze the optimal disturbance strategies and show an interesting but counterintuitive finding that disturbing “poor nodes” with low degrees preferentially is more effective than disturbing “rich nodes” with high degrees preferentially. We demonstrate the efficiency of our method by comparison with edge addition method and validate the feasibility of our method in two real-world critical infrastructure networks. |
format | Online Article Text |
id | pubmed-5548747 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-55487472017-08-09 Enhancing structural robustness of scale-free networks by information disturbance Wu, Jun Tan, Suo-Yi Liu, Zhong Tan, Yue-Jin Lu, Xin Sci Rep Article Many real-world systems can be described by scale-free networks with power-law degree distributions. Scale-free networks show a “robust yet fragile” feature due to their heterogeneous degree distributions. We propose to enhance the structural robustness of scale-free networks against intentional attacks by changing the displayed network structure information rather than modifying the network structure itself. We first introduce a simple mathematical model for attack information and investigate the impact of attack information on the structural robustness of scale-free networks. Both analytical and numerical results show that decreasing slightly the attack information perfection by information disturbance can dramatically enhance the structural robustness of scale-free networks. Then we propose an optimization model of disturbance strategies in which the cost constraint is considered. We analyze the optimal disturbance strategies and show an interesting but counterintuitive finding that disturbing “poor nodes” with low degrees preferentially is more effective than disturbing “rich nodes” with high degrees preferentially. We demonstrate the efficiency of our method by comparison with edge addition method and validate the feasibility of our method in two real-world critical infrastructure networks. Nature Publishing Group UK 2017-08-08 /pmc/articles/PMC5548747/ /pubmed/28790416 http://dx.doi.org/10.1038/s41598-017-07878-2 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Wu, Jun Tan, Suo-Yi Liu, Zhong Tan, Yue-Jin Lu, Xin Enhancing structural robustness of scale-free networks by information disturbance |
title | Enhancing structural robustness of scale-free networks by information disturbance |
title_full | Enhancing structural robustness of scale-free networks by information disturbance |
title_fullStr | Enhancing structural robustness of scale-free networks by information disturbance |
title_full_unstemmed | Enhancing structural robustness of scale-free networks by information disturbance |
title_short | Enhancing structural robustness of scale-free networks by information disturbance |
title_sort | enhancing structural robustness of scale-free networks by information disturbance |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5548747/ https://www.ncbi.nlm.nih.gov/pubmed/28790416 http://dx.doi.org/10.1038/s41598-017-07878-2 |
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