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A Microscopic-view Infection Model based on Linear Systems

Bibliographic Details
Main Author: Hao, He
Publication Date: 2019
Other Authors: Silvestre, Daniel, Silvestre, Carlos
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/11144/4313
Summary: 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:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-08-01T02:09:55Zoai:repositorio.ual.pt:11144/4313Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T18:45:10.357477Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
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
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dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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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
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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