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
Masa perjalanan pergi dan balik hujung ke hujung (RTT) ialah salah satu ciri komunikasi yang paling penting untuk aplikasi Internet. Dari sudut pandangan pengendali rangkaian, RTT juga boleh menjadi salah satu metrik penting untuk memahami keadaan rangkaian. Memandangkan latar belakang ini, kita harus tahu bagaimana faktor seperti insiden rangkaian mempengaruhi RTT. Adalah jelas bahawa dua atau lebih faktor boleh mengganggu ciri kelewatan yang diperhatikan, kerana kelewatan penghantaran paket dalam Internet sangat bergantung pada keadaan varian masa rangkaian. Dalam kertas kerja ini, kami mencadangkan kaedah pemodelan dengan menggunakan taburan campuran yang membolehkan kami menyatakan ciri kelewatan dengan lebih tepat di mana dua atau lebih faktor wujud bersama. Dan, kami juga mencadangkan kaedah inferens kelakuan rangkaian dengan penguraian taburan bercampur berdasarkan hasil pemodelan. Tambahan pula, dalam eksperimen kami menyiasat pengaruh yang disebabkan oleh setiap faktor impak rangkaian secara bebas. Kaedah cadangan kami boleh menganggap peristiwa yang berlaku dalam rangkaian daripada pengukuran RTT dengan menggunakan penguraian taburan bercampur.
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Salinan
Yasuhiro SATO, Shingo ATA, Ikuo OKA, Chikato FUJIWARA, "Inferring Network Impact Factors: Applying Mixed Distribution to Measured RTTs" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 4, pp. 1233-1243, April 2009, doi: 10.1587/transcom.E92.B.1233.
Abstract: The end-to-end round trip time (RTT) is one of the most important communication characteristics for Internet applications. From the viewpoint of network operators, RTT may also become one of the important metrics to understand the network conditions. Given this background, we should know how a factor such as a network incident influences RTTs. It is obvious that two or more factors may interfere in the observed delay characteristics, because packet transmission delays in the Internet are strongly dependent on the time-variant condition of the network. In this paper, we propose a modeling method by using mixed distribution which enables us to express delay characteristic more accurately where two or more factors exist together. And, we also propose an inferring method of network behavior by decomposition of the mixed distribution based on modeling results. Furthermore, in experiments we investigate the influence caused by each network impact factor independently. Our proposed method can presume the events that occur in a network from the measurements of RTTs by using the decomposition of the mixed distribution.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.1233/_p
Salinan
@ARTICLE{e92-b_4_1233,
author={Yasuhiro SATO, Shingo ATA, Ikuo OKA, Chikato FUJIWARA, },
journal={IEICE TRANSACTIONS on Communications},
title={Inferring Network Impact Factors: Applying Mixed Distribution to Measured RTTs},
year={2009},
volume={E92-B},
number={4},
pages={1233-1243},
abstract={The end-to-end round trip time (RTT) is one of the most important communication characteristics for Internet applications. From the viewpoint of network operators, RTT may also become one of the important metrics to understand the network conditions. Given this background, we should know how a factor such as a network incident influences RTTs. It is obvious that two or more factors may interfere in the observed delay characteristics, because packet transmission delays in the Internet are strongly dependent on the time-variant condition of the network. In this paper, we propose a modeling method by using mixed distribution which enables us to express delay characteristic more accurately where two or more factors exist together. And, we also propose an inferring method of network behavior by decomposition of the mixed distribution based on modeling results. Furthermore, in experiments we investigate the influence caused by each network impact factor independently. Our proposed method can presume the events that occur in a network from the measurements of RTTs by using the decomposition of the mixed distribution.},
keywords={},
doi={10.1587/transcom.E92.B.1233},
ISSN={1745-1345},
month={April},}
Salinan
TY - JOUR
TI - Inferring Network Impact Factors: Applying Mixed Distribution to Measured RTTs
T2 - IEICE TRANSACTIONS on Communications
SP - 1233
EP - 1243
AU - Yasuhiro SATO
AU - Shingo ATA
AU - Ikuo OKA
AU - Chikato FUJIWARA
PY - 2009
DO - 10.1587/transcom.E92.B.1233
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E92-B
IS - 4
JA - IEICE TRANSACTIONS on Communications
Y1 - April 2009
AB - The end-to-end round trip time (RTT) is one of the most important communication characteristics for Internet applications. From the viewpoint of network operators, RTT may also become one of the important metrics to understand the network conditions. Given this background, we should know how a factor such as a network incident influences RTTs. It is obvious that two or more factors may interfere in the observed delay characteristics, because packet transmission delays in the Internet are strongly dependent on the time-variant condition of the network. In this paper, we propose a modeling method by using mixed distribution which enables us to express delay characteristic more accurately where two or more factors exist together. And, we also propose an inferring method of network behavior by decomposition of the mixed distribution based on modeling results. Furthermore, in experiments we investigate the influence caused by each network impact factor independently. Our proposed method can presume the events that occur in a network from the measurements of RTTs by using the decomposition of the mixed distribution.
ER -