Anti-Pattern Specification and Correction Recommendations for Semantic Cloud Services
Molka Rekik, Khouloud Boukadi, Walid Gaaloul, Hanêne Ben‐Abdallah · Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · 2017
Given the economic and technological advantages \ they offer, cloud services are increasing being offered by \ several cloud providers. However, the lack of standardized \ descriptions of cloud services hinders their discovery. \ In an effort to standardize cloud service descriptions, \ several works propose to use ontologies. Nevertheless, \ the adoption of any of the proposed ontologies \ calls for an evaluation to show its efficiency in cloud \ service discovery. Indeed, the existing cloud providers \ describe, their similar offered services in different ways. \ Thus, various existing works aim at standardizing the \ representation of cloud computing services by proposing \ ontologies. However, since the existing proposals \ were not evaluated, they might be less adopted and considered. \ Indeed, the ontology evaluation has a direct impact \ on its understandability and reusability. In this paper, \ we propose an evaluation approach to validate our \ proposed Cloud Service Ontology (CSO), to guarantee \ an adequate cloud service discovery. To this end, this \ paper has a three-fold contribution. First, we specify a \ set of patterns and anti-patterns in order to evaluate our \ CSO. Second, we define an anti-pattern detection algorithm \ based on SPARQL queries which provides a set of \ correction recommendations to help ontologists revise \ their ontology. Finally, tests were conducted in relation \ to: (i) the algorithm efficiency and (ii) anti-pattern detection \ of design anomalies as well as taxonomic and \ domain errors within CSO.