Dynamic network clustering for scalable management of broadcast traffic in an ATM LAN

Dohoon Kim

doi:10.1109/HSNMC.2002.1032590

Dynamic network clustering for scalable management of broadcast traffic in an ATM LAN

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

Abstract

A genetic algorithm (GA) for dynamic partitioning an ATM LANE (LAN Emulation) network is presented. LANE proves to be one of the best solutions to provide guaranteed quality of service (QoS) for mid-size campus or enterprise networks with a little modification of legacy LAN facilities. However, there are few researches on efficient LANE network operations to deal with scalability issues arising from broadcast traffic delivery. To cope with this scalability issue, the proposed method is a decision model named the LANE Partitioning Problem (LPP) which aims at partitioning the entire LANE network into multiple Emulated LANs (ELANs), each of which works as an independent virtual LAN.

Original language	English
Title of host publication	5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	273-277
Number of pages	5
ISBN (Electronic)	0780376005, 9780780376007
DOIs	https://doi.org/10.1109/HSNMC.2002.1032590
Publication status	Published - 2002
Event	5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002 - Jeju Island, Korea, Republic of Duration: 3 Jul 2002 → 5 Jul 2002

Publication series

Name	5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002

Conference

Conference	5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002
Country/Territory	Korea, Republic of
City	Jeju Island
Period	3/07/02 → 5/07/02

Bibliographical note

Publisher Copyright:
© 2002 IEEE.

Access to Document

10.1109/HSNMC.2002.1032590

Cite this

Kim, D. (2002). Dynamic network clustering for scalable management of broadcast traffic in an ATM LAN. In 5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002 (pp. 273-277). Article 1032590 (5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HSNMC.2002.1032590

Kim, Dohoon. / Dynamic network clustering for scalable management of broadcast traffic in an ATM LAN. 5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002. Institute of Electrical and Electronics Engineers Inc., 2002. pp. 273-277 (5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002).

@inproceedings{b5cdf041cc4144ce9e9f5da2aba9fd2f,

title = "Dynamic network clustering for scalable management of broadcast traffic in an ATM LAN",

abstract = "A genetic algorithm (GA) for dynamic partitioning an ATM LANE (LAN Emulation) network is presented. LANE proves to be one of the best solutions to provide guaranteed quality of service (QoS) for mid-size campus or enterprise networks with a little modification of legacy LAN facilities. However, there are few researches on efficient LANE network operations to deal with scalability issues arising from broadcast traffic delivery. To cope with this scalability issue, the proposed method is a decision model named the LANE Partitioning Problem (LPP) which aims at partitioning the entire LANE network into multiple Emulated LANs (ELANs), each of which works as an independent virtual LAN.",

author = "Dohoon Kim",

note = "Publisher Copyright: {\textcopyright} 2002 IEEE.; 5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002 ; Conference date: 03-07-2002 Through 05-07-2002",

year = "2002",

doi = "10.1109/HSNMC.2002.1032590",

language = "English",

series = "5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "273--277",

booktitle = "5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002",

address = "United States",

}

Kim, D 2002, Dynamic network clustering for scalable management of broadcast traffic in an ATM LAN. in 5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002., 1032590, 5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002, Institute of Electrical and Electronics Engineers Inc., pp. 273-277, 5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002, Jeju Island, Korea, Republic of, 3/07/02. https://doi.org/10.1109/HSNMC.2002.1032590

Dynamic network clustering for scalable management of broadcast traffic in an ATM LAN. / Kim, Dohoon.
5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002. Institute of Electrical and Electronics Engineers Inc., 2002. p. 273-277 1032590 (5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002).

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

TY - GEN

T1 - Dynamic network clustering for scalable management of broadcast traffic in an ATM LAN

AU - Kim, Dohoon

PY - 2002

Y1 - 2002

N2 - A genetic algorithm (GA) for dynamic partitioning an ATM LANE (LAN Emulation) network is presented. LANE proves to be one of the best solutions to provide guaranteed quality of service (QoS) for mid-size campus or enterprise networks with a little modification of legacy LAN facilities. However, there are few researches on efficient LANE network operations to deal with scalability issues arising from broadcast traffic delivery. To cope with this scalability issue, the proposed method is a decision model named the LANE Partitioning Problem (LPP) which aims at partitioning the entire LANE network into multiple Emulated LANs (ELANs), each of which works as an independent virtual LAN.

AB - A genetic algorithm (GA) for dynamic partitioning an ATM LANE (LAN Emulation) network is presented. LANE proves to be one of the best solutions to provide guaranteed quality of service (QoS) for mid-size campus or enterprise networks with a little modification of legacy LAN facilities. However, there are few researches on efficient LANE network operations to deal with scalability issues arising from broadcast traffic delivery. To cope with this scalability issue, the proposed method is a decision model named the LANE Partitioning Problem (LPP) which aims at partitioning the entire LANE network into multiple Emulated LANs (ELANs), each of which works as an independent virtual LAN.

UR - http://www.scopus.com/inward/record.url?scp=84964264774&partnerID=8YFLogxK

U2 - 10.1109/HSNMC.2002.1032590

DO - 10.1109/HSNMC.2002.1032590

M3 - Conference contribution

AN - SCOPUS:84964264774

T3 - 5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002

SP - 273

EP - 277

BT - 5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002

Y2 - 3 July 2002 through 5 July 2002

ER -

Kim D. Dynamic network clustering for scalable management of broadcast traffic in an ATM LAN. In 5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002. Institute of Electrical and Electronics Engineers Inc. 2002. p. 273-277. 1032590. (5th IEEE International Conference on High Speed Networks and Multimedia Communications, HSNMC 2002). doi: 10.1109/HSNMC.2002.1032590

Dynamic network clustering for scalable management of broadcast traffic in an ATM LAN

Abstract

Publication series

Conference

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this