Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/41672

Anti-Pattern Specification and Correction Recommendations for Semantic Cloud Services

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Item Summary

Title: Anti-Pattern Specification and Correction Recommendations for Semantic Cloud Services
Authors: Rekik, Molka
Boukadi, Khouloud
Gaaloul, Walid
Ben-Abdallah, Hanene
Keywords: Cloud services
Description
Discovery
Evaluation
Errors and anomalies detection
show 2 moreCorrection
Patterns

show less
Issue Date: 04 Jan 2017
Abstract: 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.
Pages/Duration: 10 pages
URI/DOI: http://hdl.handle.net/10125/41672
ISBN: 978-0-9981331-0-2
DOI: 10.24251/HICSS.2017.512
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Transformation Towards Cloud Computing Minitrack



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