Joint minimization of monitoring cost and delay in overlay networks : optimal policies with a markovian approach

Vaton, Sandrine - Brun, Olivier - Mouchet, Maxime - Belzarena, Pablo - Amigo, Isabel - Prabhu, Balakrishna - Chonavel, Thierry

Resumen:

Continuous monitoring of network resources enables to make more-informed resource allocation decisions but incurs overheads. We investigate the trade-off between monitoring costs and benefits of accurate state information for a routing problem. In our approach link delays are modeled by Markov chains or hidden Markov models. The current delay information on a link can be obtained by actively monitoring this link at a fixed cost. At each time slot, the decision maker chooses to monitor a subset of links with the objective of minimizing a linear combination of long-run average delay and monitoring costs. This decision problem is modeled as a Markov decision process whose solution is computed numerically. In addition, in simple settings we prove that immediate monitoring cost and delay minimization leads to a threshold policy on a filter which sums up information from past measurements. The lightweight method as well as the optimal policy are tested on several use-cases. We demonstrate on an overlay of 30 nodes of RIPE Atlas that we obtain delay values close to the performance of the always best path with an extremely low monitoring effort when delays between nodes are modeled with hierarchical Dirichlet process hidden Markov models. Keywords : Active monitoring Routing overlays Markov chains Hidden Markov models HDP-HMM Markov decision processes Sparse monitoring Round trip times RIPE Atlas


Detalles Bibliográficos
2018
Active monitoring
Routing overlays
Markov chains
Hidden Markov models
HDP-HMM
Markov decision processes
Sparse monitoring
Round trip times
RIPE atlas
Telecomunicaciones
Inglés
Universidad de la República
COLIBRI
https://hdl.handle.net/20.500.12008/43557
Acceso abierto
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
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author Vaton, Sandrine
author2 Brun, Olivier
Mouchet, Maxime
Belzarena, Pablo
Amigo, Isabel
Prabhu, Balakrishna
Chonavel, Thierry
author2_role author
author
author
author
author
author
author_facet Vaton, Sandrine
Brun, Olivier
Mouchet, Maxime
Belzarena, Pablo
Amigo, Isabel
Prabhu, Balakrishna
Chonavel, Thierry
author_role author
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collection COLIBRI
dc.creator.none.fl_str_mv Vaton, Sandrine
Brun, Olivier
Mouchet, Maxime
Belzarena, Pablo
Amigo, Isabel
Prabhu, Balakrishna
Chonavel, Thierry
dc.date.accessioned.none.fl_str_mv 2024-04-16T16:21:31Z
dc.date.available.none.fl_str_mv 2024-04-16T16:21:31Z
dc.date.issued.es.fl_str_mv 2018
dc.date.submitted.es.fl_str_mv 20240416
dc.description.abstract.none.fl_txt_mv Continuous monitoring of network resources enables to make more-informed resource allocation decisions but incurs overheads. We investigate the trade-off between monitoring costs and benefits of accurate state information for a routing problem. In our approach link delays are modeled by Markov chains or hidden Markov models. The current delay information on a link can be obtained by actively monitoring this link at a fixed cost. At each time slot, the decision maker chooses to monitor a subset of links with the objective of minimizing a linear combination of long-run average delay and monitoring costs. This decision problem is modeled as a Markov decision process whose solution is computed numerically. In addition, in simple settings we prove that immediate monitoring cost and delay minimization leads to a threshold policy on a filter which sums up information from past measurements. The lightweight method as well as the optimal policy are tested on several use-cases. We demonstrate on an overlay of 30 nodes of RIPE Atlas that we obtain delay values close to the performance of the always best path with an extremely low monitoring effort when delays between nodes are modeled with hierarchical Dirichlet process hidden Markov models. Keywords : Active monitoring Routing overlays Markov chains Hidden Markov models HDP-HMM Markov decision processes Sparse monitoring Round trip times RIPE Atlas
dc.identifier.citation.es.fl_str_mv Vaton, S, Brun, O, Mouchet, M, Belzarena, P, Amigo, I, Prabhu, B, Chonavel, T. "Joint minimization of monitoring cost and delay in overlay networks: optimal policies with a markovian approach" [Preprint] Publicado en: Journal of Network and Systems Management, v. 27, 2019, pp.188–232 https://doi.org/10.1007/s10922-018-9464-1
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12008/43557
dc.language.iso.none.fl_str_mv en
eng
dc.rights.license.none.fl_str_mv Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:COLIBRI
instname:Universidad de la República
instacron:Universidad de la República
dc.subject.es.fl_str_mv Active monitoring
Routing overlays
Markov chains
Hidden Markov models
HDP-HMM
Markov decision processes
Sparse monitoring
Round trip times
RIPE atlas
dc.subject.other.es.fl_str_mv Telecomunicaciones
dc.title.none.fl_str_mv Joint minimization of monitoring cost and delay in overlay networks : optimal policies with a markovian approach
dc.type.es.fl_str_mv Preprint
dc.type.none.fl_str_mv info:eu-repo/semantics/preprint
dc.type.version.none.fl_str_mv info:eu-repo/semantics/submittedVersion
description Continuous monitoring of network resources enables to make more-informed resource allocation decisions but incurs overheads. We investigate the trade-off between monitoring costs and benefits of accurate state information for a routing problem. In our approach link delays are modeled by Markov chains or hidden Markov models. The current delay information on a link can be obtained by actively monitoring this link at a fixed cost. At each time slot, the decision maker chooses to monitor a subset of links with the objective of minimizing a linear combination of long-run average delay and monitoring costs. This decision problem is modeled as a Markov decision process whose solution is computed numerically. In addition, in simple settings we prove that immediate monitoring cost and delay minimization leads to a threshold policy on a filter which sums up information from past measurements. The lightweight method as well as the optimal policy are tested on several use-cases. We demonstrate on an overlay of 30 nodes of RIPE Atlas that we obtain delay values close to the performance of the always best path with an extremely low monitoring effort when delays between nodes are modeled with hierarchical Dirichlet process hidden Markov models. Keywords : Active monitoring Routing overlays Markov chains Hidden Markov models HDP-HMM Markov decision processes Sparse monitoring Round trip times RIPE Atlas
eu_rights_str_mv openAccess
format preprint
id COLIBRI_08893fb6b97d3236e1c5a833f24b515d
identifier_str_mv Vaton, S, Brun, O, Mouchet, M, Belzarena, P, Amigo, I, Prabhu, B, Chonavel, T. "Joint minimization of monitoring cost and delay in overlay networks: optimal policies with a markovian approach" [Preprint] Publicado en: Journal of Network and Systems Management, v. 27, 2019, pp.188–232 https://doi.org/10.1007/s10922-018-9464-1
instacron_str Universidad de la República
institution Universidad de la República
instname_str Universidad de la República
language eng
language_invalid_str_mv en
network_acronym_str COLIBRI
network_name_str COLIBRI
oai_identifier_str oai:colibri.udelar.edu.uy:20.500.12008/43557
publishDate 2018
reponame_str COLIBRI
repository.mail.fl_str_mv mabel.seroubian@seciu.edu.uy
repository.name.fl_str_mv COLIBRI - Universidad de la República
repository_id_str 4771
rights_invalid_str_mv Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
spelling 2024-04-16T16:21:31Z2024-04-16T16:21:31Z201820240416Vaton, S, Brun, O, Mouchet, M, Belzarena, P, Amigo, I, Prabhu, B, Chonavel, T. "Joint minimization of monitoring cost and delay in overlay networks: optimal policies with a markovian approach" [Preprint] Publicado en: Journal of Network and Systems Management, v. 27, 2019, pp.188–232 https://doi.org/10.1007/s10922-018-9464-1https://hdl.handle.net/20.500.12008/43557Continuous monitoring of network resources enables to make more-informed resource allocation decisions but incurs overheads. We investigate the trade-off between monitoring costs and benefits of accurate state information for a routing problem. In our approach link delays are modeled by Markov chains or hidden Markov models. The current delay information on a link can be obtained by actively monitoring this link at a fixed cost. At each time slot, the decision maker chooses to monitor a subset of links with the objective of minimizing a linear combination of long-run average delay and monitoring costs. This decision problem is modeled as a Markov decision process whose solution is computed numerically. In addition, in simple settings we prove that immediate monitoring cost and delay minimization leads to a threshold policy on a filter which sums up information from past measurements. The lightweight method as well as the optimal policy are tested on several use-cases. We demonstrate on an overlay of 30 nodes of RIPE Atlas that we obtain delay values close to the performance of the always best path with an extremely low monitoring effort when delays between nodes are modeled with hierarchical Dirichlet process hidden Markov models. Keywords : Active monitoring Routing overlays Markov chains Hidden Markov models HDP-HMM Markov decision processes Sparse monitoring Round trip times RIPE AtlasMade available in DSpace on 2024-04-16T16:21:31Z (GMT). No. of bitstreams: 5 VBMBAPC18.pdf: 6873354 bytes, checksum: e5dc2fa872535964fe22df08e3abf4e2 (MD5) license_text: 21936 bytes, checksum: 9833653f73f7853880c94a6fead477b1 (MD5) license_url: 49 bytes, checksum: 4afdbb8c545fd630ea7db775da747b2f (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) license.txt: 4244 bytes, checksum: 528b6a3c8c7d0c6e28129d576e989607 (MD5) Previous issue date: 2018enengLas obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)Active monitoringRouting overlaysMarkov chainsHidden Markov modelsHDP-HMMMarkov decision processesSparse monitoringRound trip timesRIPE atlasTelecomunicacionesJoint minimization of monitoring cost and delay in overlay networks : optimal policies with a markovian approachPreprintinfo:eu-repo/semantics/preprintinfo:eu-repo/semantics/submittedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaVaton, SandrineBrun, OlivierMouchet, MaximeBelzarena, PabloAmigo, IsabelPrabhu, BalakrishnaChonavel, 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spellingShingle Joint minimization of monitoring cost and delay in overlay networks : optimal policies with a markovian approach
Vaton, Sandrine
Active monitoring
Routing overlays
Markov chains
Hidden Markov models
HDP-HMM
Markov decision processes
Sparse monitoring
Round trip times
RIPE atlas
Telecomunicaciones
status_str submittedVersion
title Joint minimization of monitoring cost and delay in overlay networks : optimal policies with a markovian approach
title_full Joint minimization of monitoring cost and delay in overlay networks : optimal policies with a markovian approach
title_fullStr Joint minimization of monitoring cost and delay in overlay networks : optimal policies with a markovian approach
title_full_unstemmed Joint minimization of monitoring cost and delay in overlay networks : optimal policies with a markovian approach
title_short Joint minimization of monitoring cost and delay in overlay networks : optimal policies with a markovian approach
title_sort Joint minimization of monitoring cost and delay in overlay networks : optimal policies with a markovian approach
topic Active monitoring
Routing overlays
Markov chains
Hidden Markov models
HDP-HMM
Markov decision processes
Sparse monitoring
Round trip times
RIPE atlas
Telecomunicaciones
url https://hdl.handle.net/20.500.12008/43557