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Input graph: the hidden geometry in controlling complex networks
The ability to control a complex network towards a desired behavior relies on our understanding of the complex nature of these social and technological networks. The existence of numerous control schemes in a network promotes us to wonder: what is the underlying relationship of all possible input no...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5128914/ https://www.ncbi.nlm.nih.gov/pubmed/27901102 http://dx.doi.org/10.1038/srep38209 |
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author | Zhang, Xizhe Lv, Tianyang Pu, Yuanyuan |
author_facet | Zhang, Xizhe Lv, Tianyang Pu, Yuanyuan |
author_sort | Zhang, Xizhe |
collection | PubMed |
description | The ability to control a complex network towards a desired behavior relies on our understanding of the complex nature of these social and technological networks. The existence of numerous control schemes in a network promotes us to wonder: what is the underlying relationship of all possible input nodes? Here we introduce input graph, a simple geometry that reveals the complex relationship between all control schemes and input nodes. We prove that the node adjacent to an input node in the input graph will appear in another control scheme, and the connected nodes in input graph have the same type in control, which they are either all possible input nodes or not. Furthermore, we find that the giant components emerge in the input graphs of many real networks, which provides a clear topological explanation of bifurcation phenomenon emerging in dense networks and promotes us to design an efficient method to alter the node type in control. The findings provide an insight into control principles of complex networks and offer a general mechanism to design a suitable control scheme for different purposes. |
format | Online Article Text |
id | pubmed-5128914 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-51289142016-12-15 Input graph: the hidden geometry in controlling complex networks Zhang, Xizhe Lv, Tianyang Pu, Yuanyuan Sci Rep Article The ability to control a complex network towards a desired behavior relies on our understanding of the complex nature of these social and technological networks. The existence of numerous control schemes in a network promotes us to wonder: what is the underlying relationship of all possible input nodes? Here we introduce input graph, a simple geometry that reveals the complex relationship between all control schemes and input nodes. We prove that the node adjacent to an input node in the input graph will appear in another control scheme, and the connected nodes in input graph have the same type in control, which they are either all possible input nodes or not. Furthermore, we find that the giant components emerge in the input graphs of many real networks, which provides a clear topological explanation of bifurcation phenomenon emerging in dense networks and promotes us to design an efficient method to alter the node type in control. The findings provide an insight into control principles of complex networks and offer a general mechanism to design a suitable control scheme for different purposes. Nature Publishing Group 2016-11-30 /pmc/articles/PMC5128914/ /pubmed/27901102 http://dx.doi.org/10.1038/srep38209 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Zhang, Xizhe Lv, Tianyang Pu, Yuanyuan Input graph: the hidden geometry in controlling complex networks |
title | Input graph: the hidden geometry in controlling complex networks |
title_full | Input graph: the hidden geometry in controlling complex networks |
title_fullStr | Input graph: the hidden geometry in controlling complex networks |
title_full_unstemmed | Input graph: the hidden geometry in controlling complex networks |
title_short | Input graph: the hidden geometry in controlling complex networks |
title_sort | input graph: the hidden geometry in controlling complex networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5128914/ https://www.ncbi.nlm.nih.gov/pubmed/27901102 http://dx.doi.org/10.1038/srep38209 |
work_keys_str_mv | AT zhangxizhe inputgraphthehiddengeometryincontrollingcomplexnetworks AT lvtianyang inputgraphthehiddengeometryincontrollingcomplexnetworks AT puyuanyuan inputgraphthehiddengeometryincontrollingcomplexnetworks |