An Optimal Load Balancing Method for the Web-Server Cluster Based on the ANFIS Model

Ilseok HAN; Wanyoung KIM; Hagbae KIM

doi:10.1093/ietisy/e88-d.3.652

An Optimal Load Balancing Method for the Web-Server Cluster Based on the ANFIS Model

Ilseok HAN, Wanyoung KIM, Hagbae KIM

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This paper presents an optimal load balancing algorithm based on both of the ANFIS (Adaptive Neuro-Fuzzy Inference System) modeling and the FIS (Fuzzy Inference System) for the local status of real servers. It also shows the substantial benefits such as the removal of load-scheduling overhead, QoS (Quality of Service) provisioning and providing highly available servers, provided by the suggested method.

Publication: IEICE TRANSACTIONS on Information Vol.E88-D No.3 pp.652-653

Publication Date: 2005/03/01

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DOI: 10.1093/ietisy/e88-d.3.652

Type of Manuscript: LETTER

Category: Computer Systems

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Ilseok HAN, Wanyoung KIM, Hagbae KIM, "An Optimal Load Balancing Method for the Web-Server Cluster Based on the ANFIS Model" in IEICE TRANSACTIONS on Information, vol. E88-D, no. 3, pp. 652-653, March 2005, doi: 10.1093/ietisy/e88-d.3.652.
Abstract: This paper presents an optimal load balancing algorithm based on both of the ANFIS (Adaptive Neuro-Fuzzy Inference System) modeling and the FIS (Fuzzy Inference System) for the local status of real servers. It also shows the substantial benefits such as the removal of load-scheduling overhead, QoS (Quality of Service) provisioning and providing highly available servers, provided by the suggested method.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e88-d.3.652/_p

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@ARTICLE{e88-d_3_652,
author={Ilseok HAN, Wanyoung KIM, Hagbae KIM, },
journal={IEICE TRANSACTIONS on Information},
title={An Optimal Load Balancing Method for the Web-Server Cluster Based on the ANFIS Model},
year={2005},
volume={E88-D},
number={3},
pages={652-653},
abstract={This paper presents an optimal load balancing algorithm based on both of the ANFIS (Adaptive Neuro-Fuzzy Inference System) modeling and the FIS (Fuzzy Inference System) for the local status of real servers. It also shows the substantial benefits such as the removal of load-scheduling overhead, QoS (Quality of Service) provisioning and providing highly available servers, provided by the suggested method.},
keywords={},
doi={10.1093/ietisy/e88-d.3.652},
ISSN={},
month={March},}

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TY - JOUR
TI - An Optimal Load Balancing Method for the Web-Server Cluster Based on the ANFIS Model
T2 - IEICE TRANSACTIONS on Information
SP - 652
EP - 653
AU - Ilseok HAN
AU - Wanyoung KIM
AU - Hagbae KIM
PY - 2005
DO - 10.1093/ietisy/e88-d.3.652
JO - IEICE TRANSACTIONS on Information
SN -
VL - E88-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2005
AB - This paper presents an optimal load balancing algorithm based on both of the ANFIS (Adaptive Neuro-Fuzzy Inference System) modeling and the FIS (Fuzzy Inference System) for the local status of real servers. It also shows the substantial benefits such as the removal of load-scheduling overhead, QoS (Quality of Service) provisioning and providing highly available servers, provided by the suggested method.
ER -