The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Sur Internet, en raison de l'administration distribuée et à grande échelle, il est d'une importance pratique de déduire des caractéristiques internes au réseau qui ne peuvent pas être mesurées directement. Dans cet article, basé sur un cadre général que nous avons proposé précédemment, nous présentons une méthode réalisable pour déduire les taux de perte de paquets de liaisons individuelles à partir de la mesure de bout en bout des paquets de sonde unicast. Par rapport aux méthodes utilisant des sondes multicast, les méthodes d'inférence basées sur la monodiffusion sont plus flexibles et largement applicables, alors qu'elles rencontrent un problème de corrélation imparfaite dans les événements simultanés sur les chemins. Notre méthode peut déduire les taux de perte de liaison dans le cadre de ce problème et est applicable à diverses topologies de chemin, notamment les arbres, les arbres inverses et leurs combinaisons. Nous montrons également des résultats de simulation qui indiquent le potentiel de notre méthode basée sur la monodiffusion.
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Masato TSURU, Tetsuya TAKINE, Yuji OIE, "Inferring Link Loss Rates from Unicast-Based End-to-End Measurement" in IEICE TRANSACTIONS on Communications,
vol. E85-B, no. 1, pp. 70-78, January 2002, doi: .
Abstract: In the Internet, because of huge scale and distributed administration, it is of practical importance to infer network-internal characteristics that cannot be measured directly. In this paper, based on a general framework we proposed previously, we present a feasible method of inferring packet loss rates of individual links from end-to-end measurement of unicast probe packets. Compared with methods using multicast probes, unicast-based inference methods are more flexible and widely applicable, whereas they have a problem with imperfect correlation in concurrent events on paths. Our method can infer link loss rates under this problem, and is applicable to various path-topologies including trees, inverse trees and their combinations. We also show simulation results which indicate potential of our unicast-based method.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e85-b_1_70/_p
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@ARTICLE{e85-b_1_70,
author={Masato TSURU, Tetsuya TAKINE, Yuji OIE, },
journal={IEICE TRANSACTIONS on Communications},
title={Inferring Link Loss Rates from Unicast-Based End-to-End Measurement},
year={2002},
volume={E85-B},
number={1},
pages={70-78},
abstract={In the Internet, because of huge scale and distributed administration, it is of practical importance to infer network-internal characteristics that cannot be measured directly. In this paper, based on a general framework we proposed previously, we present a feasible method of inferring packet loss rates of individual links from end-to-end measurement of unicast probe packets. Compared with methods using multicast probes, unicast-based inference methods are more flexible and widely applicable, whereas they have a problem with imperfect correlation in concurrent events on paths. Our method can infer link loss rates under this problem, and is applicable to various path-topologies including trees, inverse trees and their combinations. We also show simulation results which indicate potential of our unicast-based method.},
keywords={},
doi={},
ISSN={},
month={January},}
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TY - JOUR
TI - Inferring Link Loss Rates from Unicast-Based End-to-End Measurement
T2 - IEICE TRANSACTIONS on Communications
SP - 70
EP - 78
AU - Masato TSURU
AU - Tetsuya TAKINE
AU - Yuji OIE
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E85-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 2002
AB - In the Internet, because of huge scale and distributed administration, it is of practical importance to infer network-internal characteristics that cannot be measured directly. In this paper, based on a general framework we proposed previously, we present a feasible method of inferring packet loss rates of individual links from end-to-end measurement of unicast probe packets. Compared with methods using multicast probes, unicast-based inference methods are more flexible and widely applicable, whereas they have a problem with imperfect correlation in concurrent events on paths. Our method can infer link loss rates under this problem, and is applicable to various path-topologies including trees, inverse trees and their combinations. We also show simulation results which indicate potential of our unicast-based method.
ER -