Distributed probabilistic input/output automata: Expressiveness, (un)decidability and algorithms

Autores
Giro, Sergio Sebastian; D'argenio, Pedro Ruben; Ferrer Fioriti, Luis Maria
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Probabilistic model checking computes the probability values of a given property quantifying over all possible schedulers. It turns out that maximum and minimum probabilities calculated in such a way are over-estimations on models of distributed systems in which components are loosely coupled and share little information with each other (and hence arbitrary schedulers may result too powerful). Therefore, we introduced definitions that characterise which are the schedulers that properly capture the idea of distributed behaviour in probabilistic and nondeterministic systems modelled as a set of interacting components. In this paper, we provide an overview of the work we have done in the last years which includes: (1) the definitions of distributed and strongly distributed schedulers, providing motivation and intuition; (2) expressiveness results, comparing them to restricted versions such as deterministic variants or finite-memory variants; (3) undecidability results—in particular the model checking problem is not decidable in general when restricting to distributed schedulers; (4) a counterexample-guided refinement technique that, using standard probabilistic model checking, allows to increase precision in the actual bounds in the distributed setting; and (5) a revision of the partial order reduction technique for probabilistic model checking. We conclude the paper with an extensive review of related work dealing with similar approaches to ours.
Fil: Giro, Sergio Sebastian. Technische Universität München; Alemania
Fil: D'argenio, Pedro Ruben. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Ferrer Fioriti, Luis Maria. Saarland University; Alemania
Materia
Probabilisstic Systems
Distributed Systems
Nondeterminism
Interleaving
Markov Decision Processes
Partial Observation
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:11336/34067
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/34067
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Distributed probabilistic input/output automata: Expressiveness, (un)decidability and algorithmsGiro, Sergio SebastianD'argenio, Pedro RubenFerrer Fioriti, Luis MariaProbabilisstic SystemsDistributed SystemsNondeterminismInterleavingMarkov Decision ProcessesPartial Observationhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Probabilistic model checking computes the probability values of a given property quantifying over all possible schedulers. It turns out that maximum and minimum probabilities calculated in such a way are over-estimations on models of distributed systems in which components are loosely coupled and share little information with each other (and hence arbitrary schedulers may result too powerful). Therefore, we introduced definitions that characterise which are the schedulers that properly capture the idea of distributed behaviour in probabilistic and nondeterministic systems modelled as a set of interacting components. In this paper, we provide an overview of the work we have done in the last years which includes: (1) the definitions of distributed and strongly distributed schedulers, providing motivation and intuition; (2) expressiveness results, comparing them to restricted versions such as deterministic variants or finite-memory variants; (3) undecidability results—in particular the model checking problem is not decidable in general when restricting to distributed schedulers; (4) a counterexample-guided refinement technique that, using standard probabilistic model checking, allows to increase precision in the actual bounds in the distributed setting; and (5) a revision of the partial order reduction technique for probabilistic model checking. We conclude the paper with an extensive review of related work dealing with similar approaches to ours.Fil: Giro, Sergio Sebastian. Technische Universität München; AlemaniaFil: D'argenio, Pedro Ruben. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ferrer Fioriti, Luis Maria. Saarland University; AlemaniaElsevier Science2014-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/34067Giro, Sergio Sebastian; D'argenio, Pedro Ruben; Ferrer Fioriti, Luis Maria; Distributed probabilistic input/output automata: Expressiveness, (un)decidability and algorithms; Elsevier Science; Theoretical Computer Science; 538; 6-2014; 84-1020304-3975CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0304397513005203info:eu-repo/semantics/altIdentifier/doi/10.1016/j.tcs.2013.07.017info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-02-26T10:22:28Zoai:ri.conicet.gov.ar:11336/34067instacron: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:34982026-02-26 10:22:28.38CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Distributed probabilistic input/output automata: Expressiveness, (un)decidability and algorithms
title Distributed probabilistic input/output automata: Expressiveness, (un)decidability and algorithms
spellingShingle Distributed probabilistic input/output automata: Expressiveness, (un)decidability and algorithms
Giro, Sergio Sebastian
Probabilisstic Systems
Distributed Systems
Nondeterminism
Interleaving
Markov Decision Processes
Partial Observation
title_short Distributed probabilistic input/output automata: Expressiveness, (un)decidability and algorithms
title_full Distributed probabilistic input/output automata: Expressiveness, (un)decidability and algorithms
title_fullStr Distributed probabilistic input/output automata: Expressiveness, (un)decidability and algorithms
title_full_unstemmed Distributed probabilistic input/output automata: Expressiveness, (un)decidability and algorithms
title_sort Distributed probabilistic input/output automata: Expressiveness, (un)decidability and algorithms
dc.creator.none.fl_str_mv Giro, Sergio Sebastian
D'argenio, Pedro Ruben
Ferrer Fioriti, Luis Maria
author Giro, Sergio Sebastian
author_facet Giro, Sergio Sebastian
D'argenio, Pedro Ruben
Ferrer Fioriti, Luis Maria
author_role author
author2 D'argenio, Pedro Ruben
Ferrer Fioriti, Luis Maria
author2_role author
author
dc.subject.none.fl_str_mv Probabilisstic Systems
Distributed Systems
Nondeterminism
Interleaving
Markov Decision Processes
Partial Observation
topic Probabilisstic Systems
Distributed Systems
Nondeterminism
Interleaving
Markov Decision Processes
Partial Observation
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Probabilistic model checking computes the probability values of a given property quantifying over all possible schedulers. It turns out that maximum and minimum probabilities calculated in such a way are over-estimations on models of distributed systems in which components are loosely coupled and share little information with each other (and hence arbitrary schedulers may result too powerful). Therefore, we introduced definitions that characterise which are the schedulers that properly capture the idea of distributed behaviour in probabilistic and nondeterministic systems modelled as a set of interacting components. In this paper, we provide an overview of the work we have done in the last years which includes: (1) the definitions of distributed and strongly distributed schedulers, providing motivation and intuition; (2) expressiveness results, comparing them to restricted versions such as deterministic variants or finite-memory variants; (3) undecidability results—in particular the model checking problem is not decidable in general when restricting to distributed schedulers; (4) a counterexample-guided refinement technique that, using standard probabilistic model checking, allows to increase precision in the actual bounds in the distributed setting; and (5) a revision of the partial order reduction technique for probabilistic model checking. We conclude the paper with an extensive review of related work dealing with similar approaches to ours.
Fil: Giro, Sergio Sebastian. Technische Universität München; Alemania
Fil: D'argenio, Pedro Ruben. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Ferrer Fioriti, Luis Maria. Saarland University; Alemania
description Probabilistic model checking computes the probability values of a given property quantifying over all possible schedulers. It turns out that maximum and minimum probabilities calculated in such a way are over-estimations on models of distributed systems in which components are loosely coupled and share little information with each other (and hence arbitrary schedulers may result too powerful). Therefore, we introduced definitions that characterise which are the schedulers that properly capture the idea of distributed behaviour in probabilistic and nondeterministic systems modelled as a set of interacting components. In this paper, we provide an overview of the work we have done in the last years which includes: (1) the definitions of distributed and strongly distributed schedulers, providing motivation and intuition; (2) expressiveness results, comparing them to restricted versions such as deterministic variants or finite-memory variants; (3) undecidability results—in particular the model checking problem is not decidable in general when restricting to distributed schedulers; (4) a counterexample-guided refinement technique that, using standard probabilistic model checking, allows to increase precision in the actual bounds in the distributed setting; and (5) a revision of the partial order reduction technique for probabilistic model checking. We conclude the paper with an extensive review of related work dealing with similar approaches to ours.
publishDate 2014
dc.date.none.fl_str_mv 2014-06
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/11336/34067
Giro, Sergio Sebastian; D'argenio, Pedro Ruben; Ferrer Fioriti, Luis Maria; Distributed probabilistic input/output automata: Expressiveness, (un)decidability and algorithms; Elsevier Science; Theoretical Computer Science; 538; 6-2014; 84-102
0304-3975
CONICET Digital
CONICET
url http://hdl.handle.net/11336/34067
identifier_str_mv Giro, Sergio Sebastian; D'argenio, Pedro Ruben; Ferrer Fioriti, Luis Maria; Distributed probabilistic input/output automata: Expressiveness, (un)decidability and algorithms; Elsevier Science; Theoretical Computer Science; 538; 6-2014; 84-102
0304-3975
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.sciencedirect.com/science/article/pii/S0304397513005203
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.tcs.2013.07.017
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
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
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 13.176822

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