Abstract
The cloud infrastructure services landscape advances steadily leaving users in the agony of choice. Therefore, we present CloudRecommender, a new declarative approach for selecting Cloud-based infrastructure services. CloudRecommender automates the mapping of users’ specified application requirements to cloud service configurations. We formally capture cloud service configurations in ontology and provide its implementation in a structured data model which can be manipulated through both regular expressions and SQL. By exploiting the power of a visual programming language (widgets), CloudRecommender further enables simplified and intuitive cloud service selection. We describe the design and a prototype implementation of CloudRecommender, and demonstrate its effectiveness and scalability through a service configuration selection experiment on most of today’s prominent cloud providers including Amazon, Azure, and GoGrid.
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Zhang, M., Ranjan, R., Menzel, M., Haller, A., Nepal, S.: A Declarative Recommender System for Cloud Infrastructure Services Selection (2012), http://arxiv.org/abs/1210.2047
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Zhang, M., Ranjan, R., Nepal, S., Menzel, M., Haller, A. (2012). A Declarative Recommender System for Cloud Infrastructure Services Selection. In: Vanmechelen, K., Altmann, J., Rana, O.F. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2012. Lecture Notes in Computer Science, vol 7714. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35194-5_8
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DOI: https://doi.org/10.1007/978-3-642-35194-5_8
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