QoS-Aware Multigranularity Service Composition: Modeling and Optimization

Quality of service (QoS)-aware optimal service composition aims to maximize the overall QoS value of the resulting composite service instance while meeting user-specified global QoS constraints. Traditional methods only consider as candidates service instances that implement one abstract service in...

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Veröffentlicht in:	IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2016-11, Vol.46 (11), p.1565-1577
Hauptverfasser:	Quanwang Wu, Ishikawa, Fuyuki, Qingsheng Zhu, Dong-Hoon Shin
Format:	Artikel
Sprache:	eng
Schlagworte:	Cities and towns Generalized component service (GCS) Genetic algorithms granularity Optimization Quality of service quality of service (QoS) Semantics service composition Weather forecasting
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container_end_page	1577
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container_title	IEEE transactions on systems, man, and cybernetics. Systems
container_volume	46
creator	Quanwang Wu Ishikawa, Fuyuki Qingsheng Zhu Dong-Hoon Shin
description	Quality of service (QoS)-aware optimal service composition aims to maximize the overall QoS value of the resulting composite service instance while meeting user-specified global QoS constraints. Traditional methods only consider as candidates service instances that implement one abstract service in the composite service and neglect those that could perform multiple abstract services. To overcome this shortcoming, this paper proposes the concept of generalized component services (GCSs), which is defined in a semantic manner, to expand the selection scope so as to achieve a better solution. A QoS-aware multigranularity service composition model is formulated and how to identify all the GCSs for a composite service is elaborated. A backtracking-based algorithm and an extended genetic algorithm are proposed to optimize the resulting composite service instance. Lastly, evaluation results of these algorithms are described.
doi_str_mv	10.1109/TSMC.2015.2503384
format	Article
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Systems</title><addtitle>TSMC</addtitle><description>Quality of service (QoS)-aware optimal service composition aims to maximize the overall QoS value of the resulting composite service instance while meeting user-specified global QoS constraints. Traditional methods only consider as candidates service instances that implement one abstract service in the composite service and neglect those that could perform multiple abstract services. To overcome this shortcoming, this paper proposes the concept of generalized component services (GCSs), which is defined in a semantic manner, to expand the selection scope so as to achieve a better solution. A QoS-aware multigranularity service composition model is formulated and how to identify all the GCSs for a composite service is elaborated. A backtracking-based algorithm and an extended genetic algorithm are proposed to optimize the resulting composite service instance. 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subjects	Cities and towns Generalized component service (GCS) Genetic algorithms granularity Optimization Quality of service quality of service (QoS) Semantics service composition Weather forecasting
title	QoS-Aware Multigranularity Service Composition: Modeling and Optimization
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