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Automating Resource Selection and Configuration in Inter-clouds through a Software Product Line Method

Abstract : Nowadays, cloud users face three important problems: (a) choosing one or more appropriate cloud provider(s) to run their application(s), (b) selecting appropriate cloud resources, which implies having enough information about the available resources, including their characteristics and constraints, and (c) configuring the cloud resources. These problems are mostly due to the wide range of resources. These resources usually have distinct dependencies, and they are offered at various clouds' layers. In this complex scenario, the users often have to handle cloud resources and their dependencies manually. This is an error-prone and time-consuming activity, even for skilled cloud users and system administrators. In this context, this paper proposes a software product line engineering (SPLE) method and a tool to deal with these issues. Our SPL-based engineering method enables a declarative and goal-oriented strategy. Furthermore, it allows resource selection and configuration in inter-cloud environments. In our proposal, the cloud users specify their applications and requirements, and our tool automatically selects and configures a suitable computing environment, taking into account temporal and functional dependencies. Experimental results on Amazon EC2 and Google Compute Engine (GCE) show that our approach enables unskilled users to have access to advanced inter-cloud computing configurations, without being concerned with the characteristics of each cloud.
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Contributor : Claire Medrala <>
Submitted on : Friday, January 8, 2016 - 3:00:26 PM
Last modification on : Wednesday, October 14, 2020 - 3:52:20 AM



Alessandro Ferreira Leite, Vladimir Castro Alves, Genaina Nunes Rodrigues, Claude Tadonki, Christine Eisenbeis, et al.. Automating Resource Selection and Configuration in Inter-clouds through a Software Product Line Method. 8th International Conference on Cloud Computing (CLOUD), 2015 IEEE , Jul 2015, New York City, United States. pp 726 - 733, ⟨10.1109/CLOUD.2015.101⟩. ⟨hal-01252985⟩



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