A network traffic model based on measurement

Dong Yan Zhang; Ming Zeng Hu; Hong L.I. Zhang; Ting Biao Kang

A network traffic model based on measurement

Dong Yan Zhang^*
, Ming Zeng Hu
, Hong L.I. Zhang
, Ting Biao Kang

^*Corresponding author for this work

Faculty of Computing

Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Network traffic and the value of performance measurement metrics can be forecasted using the traffic model. In this paper, after investigating model ARIMA which is often used in time series scopes and random process, a specific and effective method for performance forecast is presented. Through the measurement on the LAN, the data of experiment shows that the traffic model has the advantage of more forecasting precision and the traffic model is very suitable to practical operational networks.

Original language	English
Title of host publication	2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005
Pages	3857-3860
Number of pages	4
State	Published - 2005
Event	International Conference on Machine Learning and Cybernetics, ICMLC 2005 - Guangzhou, China Duration: 18 Aug 2005 → 21 Aug 2005

Publication series

Name	2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

Conference

Conference	International Conference on Machine Learning and Cybernetics, ICMLC 2005
Country/Territory	China
City	Guangzhou
Period	18/08/05 → 21/08/05

Keywords

Forecasting precision
Network measurement
Traffic forecasting
Traffic model

Cite this

@inproceedings{608a37e0d9d34c42a4e9bc0f0d39b1e4,

title = "A network traffic model based on measurement",

abstract = "Network traffic and the value of performance measurement metrics can be forecasted using the traffic model. In this paper, after investigating model ARIMA which is often used in time series scopes and random process, a specific and effective method for performance forecast is presented. Through the measurement on the LAN, the data of experiment shows that the traffic model has the advantage of more forecasting precision and the traffic model is very suitable to practical operational networks.",

keywords = "Forecasting precision, Network measurement, Traffic forecasting, Traffic model",

author = "Zhang, \{Dong Yan\} and Hu, \{Ming Zeng\} and Zhang, \{Hong L.I.\} and Kang, \{Ting Biao\}",

year = "2005",

language = "英语",

isbn = "078039092X",

series = "2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005",

pages = "3857--3860",

booktitle = "2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005",

note = "International Conference on Machine Learning and Cybernetics, ICMLC 2005 ; Conference date: 18-08-2005 Through 21-08-2005",

}

Zhang, DY, Hu, MZ, Zhang, HLI & Kang, TB 2005, A network traffic model based on measurement. in 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005. 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005, pp. 3857-3860, International Conference on Machine Learning and Cybernetics, ICMLC 2005, Guangzhou, China, 18/08/05.

A network traffic model based on measurement. / Zhang, Dong Yan; Hu, Ming Zeng; Zhang, Hong L.I. et al.
2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005. 2005. p. 3857-3860 (2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A network traffic model based on measurement

AU - Zhang, Dong Yan

AU - Hu, Ming Zeng

AU - Zhang, Hong L.I.

AU - Kang, Ting Biao

PY - 2005

Y1 - 2005

N2 - Network traffic and the value of performance measurement metrics can be forecasted using the traffic model. In this paper, after investigating model ARIMA which is often used in time series scopes and random process, a specific and effective method for performance forecast is presented. Through the measurement on the LAN, the data of experiment shows that the traffic model has the advantage of more forecasting precision and the traffic model is very suitable to practical operational networks.

AB - Network traffic and the value of performance measurement metrics can be forecasted using the traffic model. In this paper, after investigating model ARIMA which is often used in time series scopes and random process, a specific and effective method for performance forecast is presented. Through the measurement on the LAN, the data of experiment shows that the traffic model has the advantage of more forecasting precision and the traffic model is very suitable to practical operational networks.

KW - Forecasting precision

KW - Network measurement

KW - Traffic forecasting

KW - Traffic model

UR - https://www.scopus.com/pages/publications/28444499733

M3 - 会议稿件

AN - SCOPUS:28444499733

SN - 078039092X

SN - 9780780390928

T3 - 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

SP - 3857

EP - 3860

BT - 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

T2 - International Conference on Machine Learning and Cybernetics, ICMLC 2005

Y2 - 18 August 2005 through 21 August 2005

ER -

A network traffic model based on measurement

Abstract

Publication series

Conference

Keywords

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