Joint minimization of monitoring cost and delay in overlay networks : optimal policies with a markovian approach
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
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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bitstream.checksumAlgorithm.fl_str_mv | MD5 MD5 MD5 MD5 MD5 |
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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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- Universidad de la Repúblicafalse |
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 |