A Microscopic-view Infection Model based on Linear Systems
Main Author: | |
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Publication Date: | 2019 |
Other Authors: | , |
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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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 |
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 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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