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An algorithm for discovering vital nodes in regional networks based on stable path analysis
Vital node discovery is a hotspot in network topology research. The key is using the Internet’s routing characteristics to remove noisy paths and accurately describe the network topology. In this manuscript, a vital regional routing nodes discovery algorithm based on routing characteristics is propo...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10505182/ https://www.ncbi.nlm.nih.gov/pubmed/37717092 http://dx.doi.org/10.1038/s41598-023-39174-7 |
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author | Liu, Yan Liu, Yimin Liu, Fenlin Fan, Jiaxing Tao, Zhiyuan |
author_facet | Liu, Yan Liu, Yimin Liu, Fenlin Fan, Jiaxing Tao, Zhiyuan |
author_sort | Liu, Yan |
collection | PubMed |
description | Vital node discovery is a hotspot in network topology research. The key is using the Internet’s routing characteristics to remove noisy paths and accurately describe the network topology. In this manuscript, a vital regional routing nodes discovery algorithm based on routing characteristics is proposed. We analyze the stability of multiple rounds of measurement results to overcome the single vantage point’s path deviation. The unstable paths are eliminated from the regional network which is constructed through probing for target area, and the pruned topology is more in line with real routing rules. Finally, we weight the edge based on the actual network’s routing characteristics and discover vital nodes in combination with the weighting degree. Unlike existing algorithms, the proposed algorithm reconstructs the network topology based on communication and transforms unweighted network connections into weighted connections. We can evaluate the node importance in a more realistic network structure. Experiments on the Internet measurement data (275 million probing results collected in 107 days) demonstrate that: the proposed algorithm outperforms four existing typical algorithms. Among 15 groups of comparison in 3 cities, our algorithm found more (or the same number) backbone nodes in 10 groups and found more (or the same number) national backbone nodes in 13 groups. |
format | Online Article Text |
id | pubmed-10505182 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105051822023-09-18 An algorithm for discovering vital nodes in regional networks based on stable path analysis Liu, Yan Liu, Yimin Liu, Fenlin Fan, Jiaxing Tao, Zhiyuan Sci Rep Article Vital node discovery is a hotspot in network topology research. The key is using the Internet’s routing characteristics to remove noisy paths and accurately describe the network topology. In this manuscript, a vital regional routing nodes discovery algorithm based on routing characteristics is proposed. We analyze the stability of multiple rounds of measurement results to overcome the single vantage point’s path deviation. The unstable paths are eliminated from the regional network which is constructed through probing for target area, and the pruned topology is more in line with real routing rules. Finally, we weight the edge based on the actual network’s routing characteristics and discover vital nodes in combination with the weighting degree. Unlike existing algorithms, the proposed algorithm reconstructs the network topology based on communication and transforms unweighted network connections into weighted connections. We can evaluate the node importance in a more realistic network structure. Experiments on the Internet measurement data (275 million probing results collected in 107 days) demonstrate that: the proposed algorithm outperforms four existing typical algorithms. Among 15 groups of comparison in 3 cities, our algorithm found more (or the same number) backbone nodes in 10 groups and found more (or the same number) national backbone nodes in 13 groups. Nature Publishing Group UK 2023-09-16 /pmc/articles/PMC10505182/ /pubmed/37717092 http://dx.doi.org/10.1038/s41598-023-39174-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Liu, Yan Liu, Yimin Liu, Fenlin Fan, Jiaxing Tao, Zhiyuan An algorithm for discovering vital nodes in regional networks based on stable path analysis |
title | An algorithm for discovering vital nodes in regional networks based on stable path analysis |
title_full | An algorithm for discovering vital nodes in regional networks based on stable path analysis |
title_fullStr | An algorithm for discovering vital nodes in regional networks based on stable path analysis |
title_full_unstemmed | An algorithm for discovering vital nodes in regional networks based on stable path analysis |
title_short | An algorithm for discovering vital nodes in regional networks based on stable path analysis |
title_sort | algorithm for discovering vital nodes in regional networks based on stable path analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10505182/ https://www.ncbi.nlm.nih.gov/pubmed/37717092 http://dx.doi.org/10.1038/s41598-023-39174-7 |
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