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Journal of Zhejiang University SCIENCE A 2009 Vol.10 No.7 P.964~975

http://doi.org/10.1631/jzus.A0820422


Adaptive service configuration approach for quality of service management in ubiquitous computing environments


Author(s):  Yong ZHANG, Shen-sheng ZHANG, Song-qiao HAN

Affiliation(s):  Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Corresponding email(s):   zycs921@gmail.com

Key Words:  Service configuration, Ubiquitous computing (UbiComp), Quality of service (QoS), Fuzzy logic control


Yong ZHANG, Shen-sheng ZHANG, Song-qiao HAN. Adaptive service configuration approach for quality of service management in ubiquitous computing environments[J]. Journal of Zhejiang University Science A, 2009, 10(7): 964~975.

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author="Yong ZHANG, Shen-sheng ZHANG, Song-qiao HAN",
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%A Shen-sheng ZHANG
%A Song-qiao HAN
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%I Zhejiang University Press & Springer
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T1 - Adaptive service configuration approach for quality of service management in ubiquitous computing environments
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A0820422


Abstract: 
Mobility and resource-limitedness pose challenging issues to service configuration for quality of service (QoS) management in ubiquitous computing environments. Previous configuration approaches, such as static resource reservation, dynamic resource allocation and single service composition are not valid in the environments. In this study, we present an adaptive service configuration approach. Firstly, we reduce the dynamic configuration process to a control model which aims to achieve the variation of critical QoS on minimal level with less resource cost. Secondly, to deal with different QoS variations, we design two configuration strategies—service chain reconfiguration and QoS parameter adjustment—and implement them based on fuzzy logic control theory. Finally, a configuration algorithm is developed to flexibly employ the two configuration strategies in tune with the error of critical QoS in configuration process. The results of simulation experiments suggest that our approach outperforms existing configuration approaches in both QoS improvement and resource utilization.

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