Assessing diversity in multiplex networks
Diversity, understood as the variety of different elements or configurations that an extensive system has, is a crucial property that allows maintaining the system’s functionality in a changing environment, where failures, random events or malicious attacks are often unavoidable. Despite the relevan...
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| Published in: | Scientific reports Vol. 9; no. 1; p. 4511 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article Publication |
| Language: | English |
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14.03.2019
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| ISSN: | 2045-2322, 2045-2322 |
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| Abstract | Diversity, understood as the variety of different elements or configurations that an extensive system has, is a crucial property that allows maintaining the system’s functionality in a changing environment, where failures, random events or malicious attacks are often unavoidable. Despite the relevance of preserving diversity in the context of ecology, biology, transport, finances, etc., the elements or configurations that more contribute to the diversity are often unknown, and thus, they can not be protected against failures or environmental crises. This is due to the fact that there is no generic framework that allows identifying which elements or configurations have crucial roles in preserving the diversity of the system. Existing methods treat the level of heterogeneity of a system as a measure of its diversity, being unsuitable when systems are composed of a large number of elements with different attributes and types of interactions. Besides, with limited resources, one needs to find the best preservation policy, i.e., one needs to solve an optimization problem. Here we aim to bridge this gap by developing a metric between labeled graphs to compute the diversity of the system, which allows identifying the most relevant components, based on their contribution to a global diversity value. The proposed framework is suitable for large multiplex structures, which are constituted by a set of elements represented as nodes, which have different types of interactions, represented as layers. The proposed method allows us to find, in a genetic network (HIV-1), the elements with the highest diversity values, while in a European airline network, we systematically identify the companies that maximize (and those that less compromise) the variety of options for routes connecting different airports. |
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| AbstractList | Diversity, understood as the variety of different elements or configurations that an extensive system has, is a crucial property that allows maintaining the system’s functionality in a changing environment, where failures, random events or malicious attacks are often unavoidable. Despite the relevance of preserving diversity in the context of ecology, biology, transport, finances, etc., the elements or configurations that more contribute to the diversity are often unknown, and thus, they can not be protected against failures or environmental crises. This is due to the fact that there is no generic framework that allows identifying which elements or configurations have crucial roles in preserving the diversity of the system. Existing methods treat the level of heterogeneity of a system as a measure of its diversity, being unsuitable when systems are composed of a large number of elements with different attributes and types of interactions. Besides, with limited resources, one needs to find the best preservation policy, i.e., one needs to solve an optimization problem. Here we aim to bridge this gap by developing a metric between labeled graphs to compute the diversity of the system, which allows identifying the most relevant components, based on their contribution to a global diversity value. The proposed framework is suitable for large multiplex structures, which are constituted by a set of elements represented as nodes, which have different types of interactions, represented as layers. The proposed method allows us to find, in a genetic network (HIV-1), the elements with the highest diversity values, while in a European airline network, we systematically identify the companies that maximize (and those that less compromise) the variety of options for routes connecting different airports. Diversity, understood as the variety of different elements or configurations that an extensive system has, is a crucial property that allows maintaining the system’s functionality in a changing environment, where failures, random events or malicious attacks are often unavoidable. Despite the relevance of preserving diversity in the context of ecology, biology, transport, finances, etc., the elements or configurations that more contribute to the diversity are often unknown, and thus, they can not be protected against failures or environmental crises. This is due to the fact that there is no generic framework that allows identifying which elements or configurations have crucial roles in preserving the diversity of the system. Existing methods treat the level of heterogeneity of a system as a measure of its diversity, being unsuitable when systems are composed of a large number of elements with different attributes and types of interactions. Besides, with limited resources, one needs to find the best preservation policy, i.e., one needs to solve an optimization problem. Here we aim to bridge this gap by developing a metric between labeled graphs to compute the diversity of the system, which allows identifying the most relevant components, based on their contribution to a global diversity value. The proposed framework is suitable for large multiplex structures, which are constituted by a set of elements represented as nodes, which have different types of interactions, represented as layers. The proposed method allows us to find, in a genetic network (HIV-1), the elements with the highest diversity values, while in a European airline network, we systematically identify the companies that maximize (and those that less compromise) the variety of options for routes connecting different airports. Peer Reviewed Diversity, understood as the variety of different elements or configurations that an extensive system has, is a crucial property that allows maintaining the system's functionality in a changing environment, where failures, random events or malicious attacks are often unavoidable. Despite the relevance of preserving diversity in the context of ecology, biology, transport, finances, etc., the elements or configurations that more contribute to the diversity are often unknown, and thus, they can not be protected against failures or environmental crises. This is due to the fact that there is no generic framework that allows identifying which elements or configurations have crucial roles in preserving the diversity of the system. Existing methods treat the level of heterogeneity of a system as a measure of its diversity, being unsuitable when systems are composed of a large number of elements with different attributes and types of interactions. Besides, with limited resources, one needs to find the best preservation policy, i.e., one needs to solve an optimization problem. Here we aim to bridge this gap by developing a metric between labeled graphs to compute the diversity of the system, which allows identifying the most relevant components, based on their contribution to a global diversity value. The proposed framework is suitable for large multiplex structures, which are constituted by a set of elements represented as nodes, which have different types of interactions, represented as layers. The proposed method allows us to find, in a genetic network (HIV-1), the elements with the highest diversity values, while in a European airline network, we systematically identify the companies that maximize (and those that less compromise) the variety of options for routes connecting different airports.Diversity, understood as the variety of different elements or configurations that an extensive system has, is a crucial property that allows maintaining the system's functionality in a changing environment, where failures, random events or malicious attacks are often unavoidable. Despite the relevance of preserving diversity in the context of ecology, biology, transport, finances, etc., the elements or configurations that more contribute to the diversity are often unknown, and thus, they can not be protected against failures or environmental crises. This is due to the fact that there is no generic framework that allows identifying which elements or configurations have crucial roles in preserving the diversity of the system. Existing methods treat the level of heterogeneity of a system as a measure of its diversity, being unsuitable when systems are composed of a large number of elements with different attributes and types of interactions. Besides, with limited resources, one needs to find the best preservation policy, i.e., one needs to solve an optimization problem. Here we aim to bridge this gap by developing a metric between labeled graphs to compute the diversity of the system, which allows identifying the most relevant components, based on their contribution to a global diversity value. The proposed framework is suitable for large multiplex structures, which are constituted by a set of elements represented as nodes, which have different types of interactions, represented as layers. The proposed method allows us to find, in a genetic network (HIV-1), the elements with the highest diversity values, while in a European airline network, we systematically identify the companies that maximize (and those that less compromise) the variety of options for routes connecting different airports. |
| ArticleNumber | 4511 |
| Author | Masoller, Cristina Pardalos, Panos M. Ravetti, Martín G. Carpi, Laura C. Marfany, Gemma Díaz-Guilera, Albert Schieber, Tiago A. |
| Author_xml | – sequence: 1 givenname: Laura C. surname: Carpi fullname: Carpi, Laura C. organization: Programa de Pós-Graduação em Modelagem Matemática e Computacional, PPGMMC, Centro Federal de Educação Tecnológica de Minas Gerais, CEFET-MG. Av. Amazonas, 7675. 30510-000 – sequence: 2 givenname: Tiago A. surname: Schieber fullname: Schieber, Tiago A. organization: Departamento de Ciências Administrativas, Universidade Federal de Minas Gerais – sequence: 3 givenname: Panos M. surname: Pardalos fullname: Pardalos, Panos M. organization: Industrial and Systems Engineering, University of Florida – sequence: 4 givenname: Gemma surname: Marfany fullname: Marfany, Gemma organization: Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Institut de Biomedicina de la Universitat de Barcelona (IBUB-IRSJD) – sequence: 5 givenname: Cristina surname: Masoller fullname: Masoller, Cristina organization: Departament de Física, Universitat Politècnica de Catalunya – sequence: 6 givenname: Albert orcidid: 0000-0002-3114-0984 surname: Díaz-Guilera fullname: Díaz-Guilera, Albert organization: Departament de Física de la Matèria Condensada, Universitat de Barcelona, Universitat de Barcelona Institute of Complex Systems (UBICS) – sequence: 7 givenname: Martín G. orcidid: 0000-0001-7781-0034 surname: Ravetti fullname: Ravetti, Martín G. email: martin.ravetti@dep.ufmg.br organization: Departmento de Engenharia de Produção, Universidade Federal de Minas Gerais |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30872604$$D View this record in MEDLINE/PubMed |
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