Scalable monitoring heuristics for improving network latency

Mouchet, Maxime - Randall, Martín - Ségneré, Marine - Amigo, Isabel - Belzarena, Pablo - Brun, Olivier - Prabhu, Balakrishna - Vaton, Sandrine

Resumen:

We consider a routing overlay in which the delay of a path can be obtained at some fixed cost by sending probe packets, and investigate the joint minimization of the probing cost and the routing delay. Assuming that link delays are modelled by Markov chains, this problem can be cast as a Markov Decision Process (MDP). Unfortunately, computing the exact solution of this MDP is prohibitively expensive due to the well-known "curse of dimensionality". In this work we propose two scalable approaches that are fast enough to provide efficient solutions on practical time scales. We analyze the complexity of both approaches, and evaluate their accuracy in small synthetic scenarios for which the optimal monitoring policy can be computed. Finally, the robustness and the scalability of the proposed solutions are analyzed using real delay data collected over the Internet.


Detalles Bibliográficos
2020
TELECOMUNICACION
MONITORIZACION
PROCESOS DE MARKOV
REDES DE INFORMACION
Inglés
Universidad de la República
COLIBRI
https://hal.laas.fr/hal-02413636
https://hdl.handle.net/20.500.12008/23255
Acceso abierto
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
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author Mouchet, Maxime
author2 Randall, Martín
Ségneré, Marine
Amigo, Isabel
Belzarena, Pablo
Brun, Olivier
Prabhu, Balakrishna
Vaton, Sandrine
author2_role author
author
author
author
author
author
author
author_facet Mouchet, Maxime
Randall, Martín
Ségneré, Marine
Amigo, Isabel
Belzarena, Pablo
Brun, Olivier
Prabhu, Balakrishna
Vaton, Sandrine
author_role author
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collection COLIBRI
dc.contributor.filiacion.none.fl_str_mv Mouchet Maxime, IMT Atlantique, Brest, France.
Randall Martín, Universidad de la República (Uruguay). Facultad de Ingeniería.
Ségneré Marine, CNRS. LAAS - Université de Toulouse. Toulouse, France.
Amigo Isabel, IMT Atlantique, Brest, France.
Belzarena Pablo, Universidad de la República (Uruguay). Facultad de Ingeniería.
Brun Olivier, CNRS. LAAS - Université de Toulouse. Toulouse, France.
Prabhu Balakrishna, CNRS. LAAS - Université de Toulouse. Toulouse, France.
Vaton Sandrine, IMT Atlantique, Brest, France.
dc.creator.none.fl_str_mv Mouchet, Maxime
Randall, Martín
Ségneré, Marine
Amigo, Isabel
Belzarena, Pablo
Brun, Olivier
Prabhu, Balakrishna
Vaton, Sandrine
dc.date.accessioned.none.fl_str_mv 2020-03-04T16:40:31Z
dc.date.available.none.fl_str_mv 2020-03-04T16:40:31Z
dc.date.issued.none.fl_str_mv 2020
dc.description.abstract.none.fl_txt_mv We consider a routing overlay in which the delay of a path can be obtained at some fixed cost by sending probe packets, and investigate the joint minimization of the probing cost and the routing delay. Assuming that link delays are modelled by Markov chains, this problem can be cast as a Markov Decision Process (MDP). Unfortunately, computing the exact solution of this MDP is prohibitively expensive due to the well-known "curse of dimensionality". In this work we propose two scalable approaches that are fast enough to provide efficient solutions on practical time scales. We analyze the complexity of both approaches, and evaluate their accuracy in small synthetic scenarios for which the optimal monitoring policy can be computed. Finally, the robustness and the scalability of the proposed solutions are analyzed using real delay data collected over the Internet.
dc.format.extent.es.fl_str_mv 21 p.
dc.format.mimetype.es.fl_str_mv application/pdf
dc.identifier.citation.en.fl_str_mv Mouchet, M., Randall, M., Ségneré, M., y otros. Scalable monitoring heuristics for improving network latency. En: NOMS 2020. IEEE/IFIP Network Operations and Management Symposium, Budapest, Hungary : Apr. 20-24. [en línea]. Budapest : IEEE, 2020. pp. 1-21.
dc.identifier.uri.none.fl_str_mv https://hal.laas.fr/hal-02413636
https://hdl.handle.net/20.500.12008/23255
dc.language.iso.none.fl_str_mv en
eng
dc.publisher.es.fl_str_mv IEEE
dc.relation.isformatof.es.fl_str_mv PDF
dc.relation.ispartof.en.fl_str_mv NOMS 2020. IEEE/IFIP Network Operations and Management Symposium. Management in the Age of Softwarization and Artificial Intelligence, Budapest, Hungary, 20-24 apr
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.other.es.fl_str_mv TELECOMUNICACION
MONITORIZACION
PROCESOS DE MARKOV
REDES DE INFORMACION
dc.title.none.fl_str_mv Scalable monitoring heuristics for improving network latency
dc.type.es.fl_str_mv Ponencia
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
description We consider a routing overlay in which the delay of a path can be obtained at some fixed cost by sending probe packets, and investigate the joint minimization of the probing cost and the routing delay. Assuming that link delays are modelled by Markov chains, this problem can be cast as a Markov Decision Process (MDP). Unfortunately, computing the exact solution of this MDP is prohibitively expensive due to the well-known "curse of dimensionality". In this work we propose two scalable approaches that are fast enough to provide efficient solutions on practical time scales. We analyze the complexity of both approaches, and evaluate their accuracy in small synthetic scenarios for which the optimal monitoring policy can be computed. Finally, the robustness and the scalability of the proposed solutions are analyzed using real delay data collected over the Internet.
eu_rights_str_mv openAccess
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identifier_str_mv Mouchet, M., Randall, M., Ségneré, M., y otros. Scalable monitoring heuristics for improving network latency. En: NOMS 2020. IEEE/IFIP Network Operations and Management Symposium, Budapest, Hungary : Apr. 20-24. [en línea]. Budapest : IEEE, 2020. pp. 1-21.
instacron_str Universidad de la República
institution Universidad de la República
instname_str Universidad de la República
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network_acronym_str COLIBRI
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oai_identifier_str oai:colibri.udelar.edu.uy:20.500.12008/23255
publishDate 2020
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 Mouchet Maxime, IMT Atlantique, Brest, France.Randall Martín, Universidad de la República (Uruguay). Facultad de Ingeniería.Ségneré Marine, CNRS. LAAS - Université de Toulouse. Toulouse, France.Amigo Isabel, IMT Atlantique, Brest, France.Belzarena Pablo, Universidad de la República (Uruguay). Facultad de Ingeniería.Brun Olivier, CNRS. LAAS - Université de Toulouse. Toulouse, France.Prabhu Balakrishna, CNRS. LAAS - Université de Toulouse. Toulouse, France.Vaton Sandrine, IMT Atlantique, Brest, France.2020-03-04T16:40:31Z2020-03-04T16:40:31Z2020Mouchet, M., Randall, M., Ségneré, M., y otros. Scalable monitoring heuristics for improving network latency. En: NOMS 2020. IEEE/IFIP Network Operations and Management Symposium, Budapest, Hungary : Apr. 20-24. [en línea]. Budapest : IEEE, 2020. pp. 1-21.https://hal.laas.fr/hal-02413636https://hdl.handle.net/20.500.12008/23255We consider a routing overlay in which the delay of a path can be obtained at some fixed cost by sending probe packets, and investigate the joint minimization of the probing cost and the routing delay. Assuming that link delays are modelled by Markov chains, this problem can be cast as a Markov Decision Process (MDP). Unfortunately, computing the exact solution of this MDP is prohibitively expensive due to the well-known "curse of dimensionality". In this work we propose two scalable approaches that are fast enough to provide efficient solutions on practical time scales. We analyze the complexity of both approaches, and evaluate their accuracy in small synthetic scenarios for which the optimal monitoring policy can be computed. Finally, the robustness and the scalability of the proposed solutions are analyzed using real delay data collected over the Internet.Submitted by Ribeiro Jorge (jribeiro@fing.edu.uy) on 2020-02-26T21:50:02Z No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) MRSABBPV20.pdf: 825496 bytes, checksum: 612c660da55d4f1bcc62c779224916f8 (MD5)Approved for entry into archive by Machado Jimena (jmachado@fing.edu.uy) on 2020-03-04T16:29:00Z (GMT) No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) MRSABBPV20.pdf: 825496 bytes, checksum: 612c660da55d4f1bcc62c779224916f8 (MD5)Made available in DSpace by Luna Fabiana (fabiana.luna@fic.edu.uy) on 2020-03-04T16:40:31Z (GMT). No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) MRSABBPV20.pdf: 825496 bytes, checksum: 612c660da55d4f1bcc62c779224916f8 (MD5) Previous issue date: 202021 p.application/pdfenengIEEEPDFNOMS 2020. IEEE/IFIP Network Operations and Management Symposium. Management in the Age of Softwarization and Artificial Intelligence, Budapest, Hungary, 20-24 aprLas 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)TELECOMUNICACIONMONITORIZACIONPROCESOS DE MARKOVREDES DE INFORMACIONScalable monitoring heuristics for improving network latencyPonenciainfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaMouchet, MaximeRandall, MartínSégneré, MarineAmigo, IsabelBelzarena, PabloBrun, OlivierPrabhu, BalakrishnaVaton, SandrineTelecomunicacionesAnálisis de Redes, Tráfico y Estadísticas de ServiciosLICENSElicense.txtlicense.txttext/plain; charset=utf-84267http://localhost:8080/xmlui/bitstream/20.500.12008/23255/5/license.txt6429389a7df7277b72b7924fdc7d47a9MD55CC-LICENSElicense_urllicense_urltext/plain; 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- Universidad de la Repúblicafalse
spellingShingle Scalable monitoring heuristics for improving network latency
Mouchet, Maxime
TELECOMUNICACION
MONITORIZACION
PROCESOS DE MARKOV
REDES DE INFORMACION
status_str publishedVersion
title Scalable monitoring heuristics for improving network latency
title_full Scalable monitoring heuristics for improving network latency
title_fullStr Scalable monitoring heuristics for improving network latency
title_full_unstemmed Scalable monitoring heuristics for improving network latency
title_short Scalable monitoring heuristics for improving network latency
title_sort Scalable monitoring heuristics for improving network latency
topic TELECOMUNICACION
MONITORIZACION
PROCESOS DE MARKOV
REDES DE INFORMACION
url https://hal.laas.fr/hal-02413636
https://hdl.handle.net/20.500.12008/23255