DocumentCode :
2265972
Title :
Developing and managing customizable Software as a Service using feature model conversion
Author :
Moens, Hendrik ; Truyen, Eddy ; Walraven, Stefan ; Joosen, Wouter ; Dhoedt, Bart ; De Turck, Filip
Author_Institution :
Dept. of Inf. Technol., Ghent Univ. - IBBT, Ghent, Belgium
fYear :
2012
fDate :
16-20 April 2012
Firstpage :
1295
Lastpage :
1302
Abstract :
In recent years, there has been a growing interest in cloud technologies. Using current cloud solutions, it is however difficult to create customizable multi-tenant applications, especially if the application must support varying Quality of Service (QoS) guarantees. Software Product Line Engineering (SPLE) and feature modeling techniques are commonly used to address these issues in non-cloud applications, but these techniques cannot be ported directly to a cloud context, as the common approaches are geared towards customization of on-premise deployed applications, and do not support multi-tenancy. In this paper, we propose an architecture for the development and management of customizable Software as a Service (SaaS) applications, built using SPLE techniques. In our approach, each application is a composition of services, where individual services correspond to specific application functionalities, referred to as features. A feature-based methodology is described to abstract and convert the application information required at different stages of the application life-cycle: development, customization and deployment. We specifically focus on how development feature models can be adapted ensuring a one-to-one correspondence between features and services exists, ensuring the composition of services yields an application containing the corresponding features. These runtime features can then be managed using feature placement techniques. The proposed approach enables developers to define significantly less features, while limiting the amount of automatically generated features in the application runtime stage. Conversion times between models are shown to be in the order of milliseconds, while execution times of management algorithms are shown to improve by 5 to 17% depending on the application case.
Keywords :
cloud computing; life cycle costing; quality of service; software development management; software reliability; QoS guarantees; SPLE techniques; application information abstraction; application information conversion; application life-cycle; automatic feature generation; cloud technologies; customizable SaaS applications; customizable multitenant applications; customizable software as a service application development; customizable software as a service application management; feature model conversion; feature modeling techniques; feature placement techniques; feature-based methodology; quality of service; runtime features; service composition; software product line engineering; Computational modeling; Computer architecture; Engines; Quality of service; Runtime; Service oriented architecture; Clouds; Design methodology; SPLE; SaaS;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Network Operations and Management Symposium (NOMS), 2012 IEEE
Conference_Location :
Maui, HI
ISSN :
1542-1201
Print_ISBN :
978-1-4673-0267-8
Electronic_ISBN :
1542-1201
Type :
conf
DOI :
10.1109/NOMS.2012.6212066
Filename :
6212066
Link To Document :
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