Method of Estimating Short-Interval Traffic Distributions Using MIB
Summary :
Measuring traffic dynamics during intervals of a few seconds is important in the management of network performance. If the distribution of average traffic volume during a few seconds is measured, an administrator can manage the quality of the networks using the α percentile of the distribution. We propose a method of estimating the distribution of traffic volume during short intervals, such as a few seconds, by using only traffic information from the management information base (MIB) of routers or switches. This estimation method is based on traffic characteristics that are observed in traffic measurements in actual networks. It imposes little additional load on routers or switches and the computation time required to estimate the distribution is also short. Numerical examples using actual traffic data are also given.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E85-B No.5 pp.1038-1041
- Publication Date
- 2002/05/01
- Publicized
- Online ISSN
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- Type of Manuscript
- LETTER
- Category
- Network
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Takuya ASAKA, "Method of Estimating Short-Interval Traffic Distributions Using MIB" in IEICE TRANSACTIONS on Communications,
vol. E85-B, no. 5, pp. 1038-1041, May 2002, doi: .
Abstract: Measuring traffic dynamics during intervals of a few seconds is important in the management of network performance. If the distribution of average traffic volume during a few seconds is measured, an administrator can manage the quality of the networks using the α percentile of the distribution. We propose a method of estimating the distribution of traffic volume during short intervals, such as a few seconds, by using only traffic information from the management information base (MIB) of routers or switches. This estimation method is based on traffic characteristics that are observed in traffic measurements in actual networks. It imposes little additional load on routers or switches and the computation time required to estimate the distribution is also short. Numerical examples using actual traffic data are also given.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e85-b_5_1038/_p
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@ARTICLE{e85-b_5_1038,
author={Takuya ASAKA, },
journal={IEICE TRANSACTIONS on Communications},
title={Method of Estimating Short-Interval Traffic Distributions Using MIB},
year={2002},
volume={E85-B},
number={5},
pages={1038-1041},
abstract={Measuring traffic dynamics during intervals of a few seconds is important in the management of network performance. If the distribution of average traffic volume during a few seconds is measured, an administrator can manage the quality of the networks using the α percentile of the distribution. We propose a method of estimating the distribution of traffic volume during short intervals, such as a few seconds, by using only traffic information from the management information base (MIB) of routers or switches. This estimation method is based on traffic characteristics that are observed in traffic measurements in actual networks. It imposes little additional load on routers or switches and the computation time required to estimate the distribution is also short. Numerical examples using actual traffic data are also given.},
keywords={},
doi={},
ISSN={},
month={May},}
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TY - JOUR
TI - Method of Estimating Short-Interval Traffic Distributions Using MIB
T2 - IEICE TRANSACTIONS on Communications
SP - 1038
EP - 1041
AU - Takuya ASAKA
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E85-B
IS - 5
JA - IEICE TRANSACTIONS on Communications
Y1 - May 2002
AB - Measuring traffic dynamics during intervals of a few seconds is important in the management of network performance. If the distribution of average traffic volume during a few seconds is measured, an administrator can manage the quality of the networks using the α percentile of the distribution. We propose a method of estimating the distribution of traffic volume during short intervals, such as a few seconds, by using only traffic information from the management information base (MIB) of routers or switches. This estimation method is based on traffic characteristics that are observed in traffic measurements in actual networks. It imposes little additional load on routers or switches and the computation time required to estimate the distribution is also short. Numerical examples using actual traffic data are also given.
ER -
English
