Preference-Driven Refinement of Service Compositions

Cheikh Ba Umberto Costa Mirian Halfeld Ferrari 1 Rémy Ferre 2 Martin A. Musicante Veronika Peralta 3 Sophie Robert 1
1 LIFO - Laboratoire d'Informatique Fondamentale d'Orléans
2 LIFO - Laboratoire d'Informatique Fondamentale d'Orléans
3 BDTLN - Bases de données et traitement des langues naturelles
LIFAT - Laboratoire d'Informatique Fondamentale et Appliquée de Tours
Abstract : The Service Oriented Computing Paradigm proposes the construction of applications by integrating pre-existent services. Since a large number of services may be available in the Cloud, the selection of services is a crucial task in the definition of a composition. The selected services should attend the requirements of the compound application, by considering both functional and non-functional requirements (including quality and preference constraints). As the number of available services increases, the automation of the selection task becomes desirable. We propose a method for the refinement of service compositions that takes the abstract specification of a composition, the definition of concrete services and user preferences. Our algorithm produces a list of refinements in preference order. Experiments show that our method can be used in practice.
Type de document :
Communication dans un congrès
CLOSER (4th International Conference on Cloud Computing and Services Science), Apr 2014, Barcelona, Spain. 8 p., 2014, Proceedings of CLOSER 2014
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https://hal.inria.fr/hal-00978912
Contributeur : Mirian Halfeld Ferrari <>
Soumis le : lundi 14 avril 2014 - 22:44:39
Dernière modification le : jeudi 17 janvier 2019 - 15:10:02

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  • HAL Id : hal-00978912, version 1

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UNIV-ORLEANS | MSL | MSL-THESE | LIBDTLN | UNIV-TOURS | LIFAT

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Cheikh Ba, Umberto Costa, Mirian Halfeld Ferrari, Rémy Ferre, Martin A. Musicante, et al.. Preference-Driven Refinement of Service Compositions. CLOSER (4th International Conference on Cloud Computing and Services Science), Apr 2014, Barcelona, Spain. 8 p., 2014, Proceedings of CLOSER 2014. 〈hal-00978912〉

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