N. Bassiliades, M. Symeonidis, G. Meditskos, E. Kontopoulos, P. Gouvas, I. Vlahavas, "A Semantic Recommendation Algorithm for the PaaSport Platform-as-a-Service Marketplace", Expert Systems with Applications, Vol. 67, Jan. 2017, pp. 203-227.
Author(s): N. Bassiliades, M. Symeonidis, G. Meditskos, E. Kontopoulos, P. Gouvas, I. Vlahavas
Appeared In: Expert Systems with Applications, Vol. 67, Jan. 2017, pp. 203-227
Keywords: Cloud computing, Platform-as-a-Service, Semantic Interoperability, Platform offering, Cloud application, Recommendation, Semantic matchmaking, Ranking
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Abstract: Platform as a service (PaaS) is one of the Cloud computing services that provides a computing platform in the Cloud, allowing customers to develop, run, and manage web applications without the complexity of building and maintaining the infrastructure. The primary disadvantage for an SME to enter the emerging PaaS market is the possibility of being locked in to a certain platform, mostly provided by the market's giants. The PaaSport project focuses on facilitating SMEs to deploy business applications on the best-matching Cloud PaaS offering and to seamlessly migrate these applications on demand, via a thin, non-intrusive Cloud-broker, in the form of a Cloud PaaS Marketplace. PaaSport enables PaaS provider SMEs to roll out semantically interoperable PaaS offerings, by annotating them using a unified PaaS semantic model that has been defined as an OWL ontology. In this paper we focus on the recommendation algorithm that has been developed on top of the ontology, for providing the application developer with recommendations about the best-matching Cloud PaaS offering. The algorithm consists of: a) a matchmaking part, where the functional parameters of the application are taken into account to rule out inconsistent offerings, and b) a ranking part, where the non-functional parameters of the application are considered to score and rank offerings. Τhe algorithm is extensively evaluated showing linear scalability to the number of offerings and application requirements. Furthermore, it is extensible upon future semantic model extensions, because it is agnostic to domain specific concepts and parameters, using SPARQL template queries.