DocumentCode :
2487173
Title :
Using Feature Modelling and automations to select among cloud solutions
Author :
Quinten, C. ; Duchien, Laurence ; Heymans, Patrick ; Mouton, Stéphane ; Charlier, Etienne
Author_Institution :
Inria Lille - Nord Eur., Univ. Lille 1, Lille, France
fYear :
2012
fDate :
4-4 June 2012
Firstpage :
17
Lastpage :
20
Abstract :
Cloud computing is a major trend in distributed computing environments. Resources are accessed on demand by customers and are delivered as services by cloud providers in a pay-per-use model. Companies provide their applications as services and rely on cloud providers to provision, host and manage such applications on top of their infrastructure. However, the wide range of cloud solutions and the lack of knowledge in this domain is a real problem for companies when facing the cloud solution choice. In this paper, we propose to use Software Product Line Engineering (SPLE) and Feature Model (FM) configuration to develop a decision-supporting tool. Using such modelling techniques and automations, this tool takes into consideration the application technical requirements as well as the user quality requirements to provide an accurate result among cloud solutions that best fits both requirements.
Keywords :
cloud computing; decision support systems; distributed processing; FM; SPLE; cloud computing; cloud solutions; decision supporting tool; distributed computing environments; feature automations; feature model; feature modelling; pay-per-use model; quality requirements; software product line engineering; technical requirements; Cloud computing; Companies; Computational modeling; Frequency modulation; Home appliances; Servers; Cloud Computing; Feature Modelling; Separation of Concerns; Software Product Line Engineering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Product Line Approaches in Software Engineering (PLEASE), 2012 3rd International Workshop on
Conference_Location :
Zurich
Print_ISBN :
978-1-4673-1750-4
Type :
conf
DOI :
10.1109/PLEASE.2012.6229762
Filename :
6229762
Link To Document :
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