The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Este artigo propõe uma nova abordagem de configuração de serviço que pode realizar a adaptação dinâmica e crítica da Qualidade de Serviço (QoS) a ambientes de computação ubíquos em constante mudança e com recursos limitados. Na abordagem, a configuração do serviço é reduzida a um Sistema de Controle Fuzzy (FCS) que visa atingir variações críticas de QoS em um nível mínimo com menor custo de energia. Duas estratégias de configuração, reconfiguração da cadeia de serviço e ajuste de parâmetros de QoS, juntamente com um algoritmo de configuração, são implementadas para lidar com diferentes tipos de variações de QoS. Um algoritmo de auto-otimização é projetado para melhorar a adaptação do FCS. Os resultados da simulação validam a abordagem proposta.
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Yong ZHANG, Shensheng ZHANG, Songqiao HAN, "A Fuzzy Control-Based Service Configuration Approach for Ubiquitous Computing Applications" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 5, pp. 1186-1189, May 2009, doi: 10.1587/transinf.E92.D.1186.
Abstract: This paper proposes a novel service configuration approach that can realize dynamic critical Quality of Service (QoS) adaptation to ever-changing and resource-limited ubiquitous computing environments. In the approach, service configuration is reduced to a Fuzzy Control System (FCS) which aims to achieve critical QoS variations on minimal level with less power cost. Two configuration strategies, service chain reconfiguration and QoS parameters adjustment, along with a configuration algorithm, are implemented to handle different types of QoS variations. A self-optimizing algorithm is designed to enhance the adaptation of the FCS. Simulation results validate the proposed approach.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.1186/_p
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@ARTICLE{e92-d_5_1186,
author={Yong ZHANG, Shensheng ZHANG, Songqiao HAN, },
journal={IEICE TRANSACTIONS on Information},
title={A Fuzzy Control-Based Service Configuration Approach for Ubiquitous Computing Applications},
year={2009},
volume={E92-D},
number={5},
pages={1186-1189},
abstract={This paper proposes a novel service configuration approach that can realize dynamic critical Quality of Service (QoS) adaptation to ever-changing and resource-limited ubiquitous computing environments. In the approach, service configuration is reduced to a Fuzzy Control System (FCS) which aims to achieve critical QoS variations on minimal level with less power cost. Two configuration strategies, service chain reconfiguration and QoS parameters adjustment, along with a configuration algorithm, are implemented to handle different types of QoS variations. A self-optimizing algorithm is designed to enhance the adaptation of the FCS. Simulation results validate the proposed approach.},
keywords={},
doi={10.1587/transinf.E92.D.1186},
ISSN={1745-1361},
month={May},}
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TY - JOUR
TI - A Fuzzy Control-Based Service Configuration Approach for Ubiquitous Computing Applications
T2 - IEICE TRANSACTIONS on Information
SP - 1186
EP - 1189
AU - Yong ZHANG
AU - Shensheng ZHANG
AU - Songqiao HAN
PY - 2009
DO - 10.1587/transinf.E92.D.1186
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2009
AB - This paper proposes a novel service configuration approach that can realize dynamic critical Quality of Service (QoS) adaptation to ever-changing and resource-limited ubiquitous computing environments. In the approach, service configuration is reduced to a Fuzzy Control System (FCS) which aims to achieve critical QoS variations on minimal level with less power cost. Two configuration strategies, service chain reconfiguration and QoS parameters adjustment, along with a configuration algorithm, are implemented to handle different types of QoS variations. A self-optimizing algorithm is designed to enhance the adaptation of the FCS. Simulation results validate the proposed approach.
ER -