A Microscopic-view Infection Model based on Linear Systems

Detalhes bibliográficos
Autor(a) principal: Hao, He
Data de Publicação: 2019
Outros Autores: Silvestre, Daniel, Silvestre, Carlos
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/11144/4313
Resumo: Understanding the behavior of an infection network is typically addressed from either a microscopic or a macroscopic point-of-view. The trade-off is between following the individual states at some added complexity cost or looking at the ratio of infected nodes. In this paper, we focus on developing an alternative approach based on dynamical linear systems that combines the fine information of the microscopic view without the associated added complexity. Attention is shifted towards the problems of source localization and network topology discovery in the context of infection networks where a subset of the nodes is elected as observers. Finally, the possibility to control such networks is also investigated. Simulations illustrate the conclusions of the paper with particular interest on the relationship of the aforementioned problems with the topology of the network and the selected observer/controller nodes.
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spelling A Microscopic-view Infection Model based on Linear SystemsInfection networksSource localizationTopology identificationLinear modelsControllabilityObservabilityUnderstanding the behavior of an infection network is typically addressed from either a microscopic or a macroscopic point-of-view. The trade-off is between following the individual states at some added complexity cost or looking at the ratio of infected nodes. In this paper, we focus on developing an alternative approach based on dynamical linear systems that combines the fine information of the microscopic view without the associated added complexity. Attention is shifted towards the problems of source localization and network topology discovery in the context of infection networks where a subset of the nodes is elected as observers. Finally, the possibility to control such networks is also investigated. Simulations illustrate the conclusions of the paper with particular interest on the relationship of the aforementioned problems with the topology of the network and the selected observer/controller nodes.Elsevier2019-09-19T17:15:13Z2019-01-01T00:00:00Z2019info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/11144/4313eng0020-0255https://doi.org/10.1016/j.ins.2019.09.021Hao, HeSilvestre, DanielSilvestre, Carlosinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-11T02:25:08Zoai:repositorio.ual.pt:11144/4313Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:35:04.970224Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A Microscopic-view Infection Model based on Linear Systems
title A Microscopic-view Infection Model based on Linear Systems
spellingShingle A Microscopic-view Infection Model based on Linear Systems
Hao, He
Infection networks
Source localization
Topology identification
Linear models
Controllability
Observability
title_short A Microscopic-view Infection Model based on Linear Systems
title_full A Microscopic-view Infection Model based on Linear Systems
title_fullStr A Microscopic-view Infection Model based on Linear Systems
title_full_unstemmed A Microscopic-view Infection Model based on Linear Systems
title_sort A Microscopic-view Infection Model based on Linear Systems
author Hao, He
author_facet Hao, He
Silvestre, Daniel
Silvestre, Carlos
author_role author
author2 Silvestre, Daniel
Silvestre, Carlos
author2_role author
author
dc.contributor.author.fl_str_mv Hao, He
Silvestre, Daniel
Silvestre, Carlos
dc.subject.por.fl_str_mv Infection networks
Source localization
Topology identification
Linear models
Controllability
Observability
topic Infection networks
Source localization
Topology identification
Linear models
Controllability
Observability
description Understanding the behavior of an infection network is typically addressed from either a microscopic or a macroscopic point-of-view. The trade-off is between following the individual states at some added complexity cost or looking at the ratio of infected nodes. In this paper, we focus on developing an alternative approach based on dynamical linear systems that combines the fine information of the microscopic view without the associated added complexity. Attention is shifted towards the problems of source localization and network topology discovery in the context of infection networks where a subset of the nodes is elected as observers. Finally, the possibility to control such networks is also investigated. Simulations illustrate the conclusions of the paper with particular interest on the relationship of the aforementioned problems with the topology of the network and the selected observer/controller nodes.
publishDate 2019
dc.date.none.fl_str_mv 2019-09-19T17:15:13Z
2019-01-01T00:00:00Z
2019
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/11144/4313
url http://hdl.handle.net/11144/4313
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0020-0255
https://doi.org/10.1016/j.ins.2019.09.021
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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