Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds

Autores
Di Muro, Matias Alberto; Valdez, Lucas Daniel; Aragão Rêgo, H. H.; Buldyrev, S. V.; Stanley, H. E.; Braunstein, Lidia Adriana
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Various social, financial, biological and technological systems can be modeled by interdependent networks. It has been assumed that in order to remain functional, nodes in one network must receive the support from nodes belonging to different networks. So far these models have been limited to the case in which the failure propagates across networks only if the nodes lose all their supply nodes. In this paper we develop a more realistic model for two interdependent networks in which each node has its own supply threshold, i.e., they need the support of a minimum number of supply nodes to remain functional. In addition, we analyze different conditions of internal node failure due to disconnection from nodes within its own network. We show that several local internal failure conditions lead to similar nontrivial results. When there are no internal failures the model is equivalent to a bipartite system, which can be useful to model a financial market. We explore the rich behaviors of these models that include discontinuous and continuous phase transitions. Using the generating functions formalism, we analytically solve all the models in the limit of infinitely large networks and find an excellent agreement with the stochastic simulations.
Fil: Di Muro, Matias Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Físicas de Mar del Plata. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Físicas de Mar del Plata; Argentina
Fil: Valdez, Lucas Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina
Fil: Aragão Rêgo, H. H.. Instituto Federal de Educação, Ciência e Tecnologia do Maranhão; Brasil
Fil: Buldyrev, S. V.. Yeshiva University; Estados Unidos
Fil: Stanley, H. E.. Boston University; Estados Unidos
Fil: Braunstein, Lidia Adriana. Boston University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Físicas de Mar del Plata. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Físicas de Mar del Plata; Argentina
Materia
Complex Networks
Cascading Failures
Percolation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/64745
Acceder
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spelling Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality ThresholdsDi Muro, Matias AlbertoValdez, Lucas DanielAragão Rêgo, H. H.Buldyrev, S. V.Stanley, H. E.Braunstein, Lidia AdrianaComplex NetworksCascading FailuresPercolationhttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1https://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1Various social, financial, biological and technological systems can be modeled by interdependent networks. It has been assumed that in order to remain functional, nodes in one network must receive the support from nodes belonging to different networks. So far these models have been limited to the case in which the failure propagates across networks only if the nodes lose all their supply nodes. In this paper we develop a more realistic model for two interdependent networks in which each node has its own supply threshold, i.e., they need the support of a minimum number of supply nodes to remain functional. In addition, we analyze different conditions of internal node failure due to disconnection from nodes within its own network. We show that several local internal failure conditions lead to similar nontrivial results. When there are no internal failures the model is equivalent to a bipartite system, which can be useful to model a financial market. We explore the rich behaviors of these models that include discontinuous and continuous phase transitions. Using the generating functions formalism, we analytically solve all the models in the limit of infinitely large networks and find an excellent agreement with the stochastic simulations.Fil: Di Muro, Matias Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Físicas de Mar del Plata. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Físicas de Mar del Plata; ArgentinaFil: Valdez, Lucas Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; ArgentinaFil: Aragão Rêgo, H. H.. Instituto Federal de Educação, Ciência e Tecnologia do Maranhão; BrasilFil: Buldyrev, S. V.. Yeshiva University; Estados UnidosFil: Stanley, H. E.. Boston University; Estados UnidosFil: Braunstein, Lidia Adriana. Boston University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Físicas de Mar del Plata. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Físicas de Mar del Plata; ArgentinaNature Publishing Group2017-12-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/64745Di Muro, Matias Alberto; Valdez, Lucas Daniel; Aragão Rêgo, H. H.; Buldyrev, S. V.; Stanley, H. E.; et al.; Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds; Nature Publishing Group; Scientific Reports; 7; 1; 8-12-2017; 1-102045-2322CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.nature.com/articles/s41598-017-14384-yinfo:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-017-14384-yinfo:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/abs/1708.00428info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:43:04Zoai:ri.conicet.gov.ar:11336/64745instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 15:43:04.538CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds
title Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds
spellingShingle Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds
Di Muro, Matias Alberto
Complex Networks
Cascading Failures
Percolation
title_short Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds
title_full Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds
title_fullStr Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds
title_full_unstemmed Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds
title_sort Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds
dc.creator.none.fl_str_mv Di Muro, Matias Alberto
Valdez, Lucas Daniel
Aragão Rêgo, H. H.
Buldyrev, S. V.
Stanley, H. E.
Braunstein, Lidia Adriana
author Di Muro, Matias Alberto
author_facet Di Muro, Matias Alberto
Valdez, Lucas Daniel
Aragão Rêgo, H. H.
Buldyrev, S. V.
Stanley, H. E.
Braunstein, Lidia Adriana
author_role author
author2 Valdez, Lucas Daniel
Aragão Rêgo, H. H.
Buldyrev, S. V.
Stanley, H. E.
Braunstein, Lidia Adriana
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Complex Networks
Cascading Failures
Percolation
topic Complex Networks
Cascading Failures
Percolation
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Various social, financial, biological and technological systems can be modeled by interdependent networks. It has been assumed that in order to remain functional, nodes in one network must receive the support from nodes belonging to different networks. So far these models have been limited to the case in which the failure propagates across networks only if the nodes lose all their supply nodes. In this paper we develop a more realistic model for two interdependent networks in which each node has its own supply threshold, i.e., they need the support of a minimum number of supply nodes to remain functional. In addition, we analyze different conditions of internal node failure due to disconnection from nodes within its own network. We show that several local internal failure conditions lead to similar nontrivial results. When there are no internal failures the model is equivalent to a bipartite system, which can be useful to model a financial market. We explore the rich behaviors of these models that include discontinuous and continuous phase transitions. Using the generating functions formalism, we analytically solve all the models in the limit of infinitely large networks and find an excellent agreement with the stochastic simulations.
Fil: Di Muro, Matias Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Físicas de Mar del Plata. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Físicas de Mar del Plata; Argentina
Fil: Valdez, Lucas Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina
Fil: Aragão Rêgo, H. H.. Instituto Federal de Educação, Ciência e Tecnologia do Maranhão; Brasil
Fil: Buldyrev, S. V.. Yeshiva University; Estados Unidos
Fil: Stanley, H. E.. Boston University; Estados Unidos
Fil: Braunstein, Lidia Adriana. Boston University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Físicas de Mar del Plata. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Físicas de Mar del Plata; Argentina
description Various social, financial, biological and technological systems can be modeled by interdependent networks. It has been assumed that in order to remain functional, nodes in one network must receive the support from nodes belonging to different networks. So far these models have been limited to the case in which the failure propagates across networks only if the nodes lose all their supply nodes. In this paper we develop a more realistic model for two interdependent networks in which each node has its own supply threshold, i.e., they need the support of a minimum number of supply nodes to remain functional. In addition, we analyze different conditions of internal node failure due to disconnection from nodes within its own network. We show that several local internal failure conditions lead to similar nontrivial results. When there are no internal failures the model is equivalent to a bipartite system, which can be useful to model a financial market. We explore the rich behaviors of these models that include discontinuous and continuous phase transitions. Using the generating functions formalism, we analytically solve all the models in the limit of infinitely large networks and find an excellent agreement with the stochastic simulations.
publishDate 2017
dc.date.none.fl_str_mv 2017-12-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/64745
Di Muro, Matias Alberto; Valdez, Lucas Daniel; Aragão Rêgo, H. H.; Buldyrev, S. V.; Stanley, H. E.; et al.; Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds; Nature Publishing Group; Scientific Reports; 7; 1; 8-12-2017; 1-10
2045-2322
CONICET Digital
CONICET
url http://hdl.handle.net/11336/64745
identifier_str_mv Di Muro, Matias Alberto; Valdez, Lucas Daniel; Aragão Rêgo, H. H.; Buldyrev, S. V.; Stanley, H. E.; et al.; Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds; Nature Publishing Group; Scientific Reports; 7; 1; 8-12-2017; 1-10
2045-2322
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.nature.com/articles/s41598-017-14384-y
info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-017-14384-y
info:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/abs/1708.00428
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Nature Publishing Group
publisher.none.fl_str_mv Nature Publishing Group
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.22299

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