SALOON: a platform for selecting and ...
Type de document :
Article dans une revue scientifique
DOI :
URL permanente :
Titre :
SALOON: a platform for selecting and configuring cloud environments
Auteur(s) :
Quinton, Clément [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Romero Acero, Daniel [Auteur]
Duchien, Laurence [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Romero Acero, Daniel [Auteur]
Duchien, Laurence [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Titre de la revue :
Software. Practice and Experience
Numéro :
46
Pagination :
55-78
Date de publication :
2015-01-13
Résumé en anglais : [en]
Migrating legacy systems or deploying a new application to a cloud environment has recently become very trendy, because the number of cloud providers available is still increasing. These cloud environments provide a wide ...
Lire la suite >Migrating legacy systems or deploying a new application to a cloud environment has recently become very trendy, because the number of cloud providers available is still increasing. These cloud environments provide a wide range of resources at different levels of functionality, which must be appropriately configured by stakeholders for the application to run properly. Handling this variability during the configuration and deployment stages is known as a complex and error-prone process, usually made in an ad hoc manner. In this paper, we propose SALOON, a software product lines-based platform to face these issues. We describe the architecture of the SALOON platform, which relies on feature models combined with a domain model used to select among cloud environments a well-suited one. SALOON supports stakeholders while configuring the selected cloud environment in a consistent way and automates the deployment of such configurations through the generation of executable configuration scripts. This paper also reports on some experiments, showing that using SALOON significantly reduces time to configure a cloud environment compared with a manual approach and provides a reliable way to find a correct and suitable configuration. Moreover, our empirical evaluation shows that our approach is effective and scalable to properly deal with a significant number of cloud environments.Lire moins >
Lire la suite >Migrating legacy systems or deploying a new application to a cloud environment has recently become very trendy, because the number of cloud providers available is still increasing. These cloud environments provide a wide range of resources at different levels of functionality, which must be appropriately configured by stakeholders for the application to run properly. Handling this variability during the configuration and deployment stages is known as a complex and error-prone process, usually made in an ad hoc manner. In this paper, we propose SALOON, a software product lines-based platform to face these issues. We describe the architecture of the SALOON platform, which relies on feature models combined with a domain model used to select among cloud environments a well-suited one. SALOON supports stakeholders while configuring the selected cloud environment in a consistent way and automates the deployment of such configurations through the generation of executable configuration scripts. This paper also reports on some experiments, showing that using SALOON significantly reduces time to configure a cloud environment compared with a manual approach and provides a reliable way to find a correct and suitable configuration. Moreover, our empirical evaluation shows that our approach is effective and scalable to properly deal with a significant number of cloud environments.Lire moins >
Langue :
Anglais
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
ENSCL
CNRS
Centrale Lille
Univ. Artois
Université de Lille
CNRS
Centrale Lille
Univ. Artois
Université de Lille
Collections :
Date de dépôt :
2019-09-25T14:05:58Z