A declarative recommender system for cloud infrastructure services selection

Authors:
Miranda Zhang;Rajiv Ranjan;Surya Nepal;Michael Menzel;Armin Haller
Affiliations:
Information Engineering Laboratory, CSIRO ICT Centre, Australia;Information Engineering Laboratory, CSIRO ICT Centre, Australia;Information Engineering Laboratory, CSIRO ICT Centre, Australia;Karlsruhe Institute of Technology, Karlsruhe, Germany;Information Engineering Laboratory, CSIRO ICT Centre, Australia
Venue:
GECON'12 Proceedings of the 9th international conference on Economics of Grids, Clouds, Systems, and Services
Year:
2012

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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.