A Long Range Dependent Internet Traffic Model Using Unbounded Johnson Distribution
Summary :
It is important to characterize the distributional property and the long-range dependency of traffic arrival processes in modeling Internet traffic. To address this problem, we propose a long-range dependent traffic model using the unbounded Johnson distribution. Using the proposed model, a sequence of traffic rates with the desired four quantiles and Hurst parameter can be generated. Numerical studies show how well the sequence of traffic rates generated by the proposed model mimics that of the real traffic rates using a publicly available Internet traffic trace.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E96-B No.1 pp.301-304
- Publication Date
- 2013/01/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E96.B.301
- Type of Manuscript
- LETTER
- Category
- Fundamental Theories for Communications
Authors
Keyword
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Sunggon KIM, Seung Yeob NAM, "A Long Range Dependent Internet Traffic Model Using Unbounded Johnson Distribution" in IEICE TRANSACTIONS on Communications,
vol. E96-B, no. 1, pp. 301-304, January 2013, doi: 10.1587/transcom.E96.B.301.
Abstract: It is important to characterize the distributional property and the long-range dependency of traffic arrival processes in modeling Internet traffic. To address this problem, we propose a long-range dependent traffic model using the unbounded Johnson distribution. Using the proposed model, a sequence of traffic rates with the desired four quantiles and Hurst parameter can be generated. Numerical studies show how well the sequence of traffic rates generated by the proposed model mimics that of the real traffic rates using a publicly available Internet traffic trace.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E96.B.301/_p
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@ARTICLE{e96-b_1_301,
author={Sunggon KIM, Seung Yeob NAM, },
journal={IEICE TRANSACTIONS on Communications},
title={A Long Range Dependent Internet Traffic Model Using Unbounded Johnson Distribution},
year={2013},
volume={E96-B},
number={1},
pages={301-304},
abstract={It is important to characterize the distributional property and the long-range dependency of traffic arrival processes in modeling Internet traffic. To address this problem, we propose a long-range dependent traffic model using the unbounded Johnson distribution. Using the proposed model, a sequence of traffic rates with the desired four quantiles and Hurst parameter can be generated. Numerical studies show how well the sequence of traffic rates generated by the proposed model mimics that of the real traffic rates using a publicly available Internet traffic trace.},
keywords={},
doi={10.1587/transcom.E96.B.301},
ISSN={1745-1345},
month={January},}
Copy
TY - JOUR
TI - A Long Range Dependent Internet Traffic Model Using Unbounded Johnson Distribution
T2 - IEICE TRANSACTIONS on Communications
SP - 301
EP - 304
AU - Sunggon KIM
AU - Seung Yeob NAM
PY - 2013
DO - 10.1587/transcom.E96.B.301
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E96-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 2013
AB - It is important to characterize the distributional property and the long-range dependency of traffic arrival processes in modeling Internet traffic. To address this problem, we propose a long-range dependent traffic model using the unbounded Johnson distribution. Using the proposed model, a sequence of traffic rates with the desired four quantiles and Hurst parameter can be generated. Numerical studies show how well the sequence of traffic rates generated by the proposed model mimics that of the real traffic rates using a publicly available Internet traffic trace.
ER -
English
