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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Bibliographic Details
Published in:IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2016-11, Vol.46 (11), p.1565-1577
Main Authors: Quanwang Wu, Ishikawa, Fuyuki, Qingsheng Zhu, Dong-Hoon Shin
Format: Article
Language:English
Subjects:
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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Summary: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.
ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2015.2503384