The modeling and traffic feedback control for QoS management on local network

Jongjin Park; E. N. Huh; Y. Mun; B. G. Lee

doi:10.1007/3-540-44843-8_50

The modeling and traffic feedback control for QoS management on local network

Jongjin Park, E. N. Huh, Y. Mun, B. G. Lee

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

Abstract

Throughput response characteristics depending on the network bandwidth allocation is needed to be modeled to devise adaptive control mechanism to support QoS of the local network. In this study, we propose a dynamic system model that reveals the response characteristics of network. The adaptive traffic feedback control is applied to this model. And we simulate this system for optimization of adaptive control mechanism. Finally, we implement optimized adaptive control mechanism to the real network. Therefore we observe a good performance with adaptive control mechanism to support QoS of network.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editors	Vipin Kumar, Vipin Kumar, Marina L. Gavrilova, Chih Jeng Kenneth Tan, Chih Jeng Kenneth Tan, Pierre L’Ecuyer
Publisher	Springer Verlag
Pages	463-471
Number of pages	9
ISBN (Print)	354040161X
DOIs	https://doi.org/10.1007/3-540-44843-8_50
Publication status	Published - 2003

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2668
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Access to Document

10.1007/3-540-44843-8_50

Cite this

Park, J., Huh, E. N., Mun, Y., & Lee, B. G. (2003). The modeling and traffic feedback control for QoS management on local network. In V. Kumar, V. Kumar, M. L. Gavrilova, C. J. K. Tan, C. J. K. Tan, & P. L’Ecuyer (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 463-471). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2668). Springer Verlag. https://doi.org/10.1007/3-540-44843-8_50

Park, Jongjin ; Huh, E. N. ; Mun, Y. et al. / The modeling and traffic feedback control for QoS management on local network. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Vipin Kumar ; Vipin Kumar ; Marina L. Gavrilova ; Chih Jeng Kenneth Tan ; Chih Jeng Kenneth Tan ; Pierre L’Ecuyer. Springer Verlag, 2003. pp. 463-471 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inbook{be2ef6d8f692407e831473664a17dc53,

title = "The modeling and traffic feedback control for QoS management on local network",

abstract = "Throughput response characteristics depending on the network bandwidth allocation is needed to be modeled to devise adaptive control mechanism to support QoS of the local network. In this study, we propose a dynamic system model that reveals the response characteristics of network. The adaptive traffic feedback control is applied to this model. And we simulate this system for optimization of adaptive control mechanism. Finally, we implement optimized adaptive control mechanism to the real network. Therefore we observe a good performance with adaptive control mechanism to support QoS of network.",

author = "Jongjin Park and Huh, {E. N.} and Y. Mun and Lee, {B. G.}",

year = "2003",

doi = "10.1007/3-540-44843-8_50",

language = "English",

isbn = "354040161X",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "463--471",

editor = "Vipin Kumar and Vipin Kumar and Gavrilova, {Marina L.} and Tan, {Chih Jeng Kenneth} and Tan, {Chih Jeng Kenneth} and Pierre L{\textquoteright}Ecuyer",

booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

address = "Germany",

}

Park, J, Huh, EN, Mun, Y & Lee, BG 2003, The modeling and traffic feedback control for QoS management on local network. in V Kumar, V Kumar, ML Gavrilova, CJK Tan, CJK Tan & P L’Ecuyer (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2668, Springer Verlag, pp. 463-471. https://doi.org/10.1007/3-540-44843-8_50

The modeling and traffic feedback control for QoS management on local network. / Park, Jongjin; Huh, E. N.; Mun, Y. et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Vipin Kumar; Vipin Kumar; Marina L. Gavrilova; Chih Jeng Kenneth Tan; Chih Jeng Kenneth Tan; Pierre L’Ecuyer. Springer Verlag, 2003. p. 463-471 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2668).

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

TY - CHAP

T1 - The modeling and traffic feedback control for QoS management on local network

AU - Park, Jongjin

AU - Huh, E. N.

AU - Mun, Y.

AU - Lee, B. G.

PY - 2003

Y1 - 2003

N2 - Throughput response characteristics depending on the network bandwidth allocation is needed to be modeled to devise adaptive control mechanism to support QoS of the local network. In this study, we propose a dynamic system model that reveals the response characteristics of network. The adaptive traffic feedback control is applied to this model. And we simulate this system for optimization of adaptive control mechanism. Finally, we implement optimized adaptive control mechanism to the real network. Therefore we observe a good performance with adaptive control mechanism to support QoS of network.

AB - Throughput response characteristics depending on the network bandwidth allocation is needed to be modeled to devise adaptive control mechanism to support QoS of the local network. In this study, we propose a dynamic system model that reveals the response characteristics of network. The adaptive traffic feedback control is applied to this model. And we simulate this system for optimization of adaptive control mechanism. Finally, we implement optimized adaptive control mechanism to the real network. Therefore we observe a good performance with adaptive control mechanism to support QoS of network.

UR - http://www.scopus.com/inward/record.url?scp=35248866293&partnerID=8YFLogxK

U2 - 10.1007/3-540-44843-8_50

DO - 10.1007/3-540-44843-8_50

M3 - Chapter

AN - SCOPUS:35248866293

SN - 354040161X

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 463

EP - 471

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

A2 - Kumar, Vipin

A2 - Gavrilova, Marina L.

A2 - Tan, Chih Jeng Kenneth

A2 - L’Ecuyer, Pierre

PB - Springer Verlag

ER -

Park J, Huh EN, Mun Y, Lee BG. The modeling and traffic feedback control for QoS management on local network. In Kumar V, Kumar V, Gavrilova ML, Tan CJK, Tan CJK, L’Ecuyer P, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2003. p. 463-471. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-44843-8_50

The modeling and traffic feedback control for QoS management on local network

Abstract

Publication series

Access to Document

Other files and links

Fingerprint

Cite this