Title: Ontology-based web services classification for registration and discovery of web services

Authors: Moussa Kaouan; Djelloul Bouchiha; Sidi Mohamed Benslimane; Sofiane Boukli Hacene

Addresses: Faculty of Sciences, Department of Computer Science, EEDIS Lab, University Djillali Liabes of Sidi Bel-abbes, Algeria ' Department Mathematics and Computer Science, Inst. Sciences and Technologies, Ctr Univ Naama, Algeria ' LabRI-SBA Lab., École Supérieure en Informatique, Sidi Bel Abbes, Algeria ' EEDIS Lab., University Djillali Liabes of Sidi Bel Abbes, Algeria

Abstract: Web services become increasingly important in the world of internet. Thus, users need to access and effectively share web services. The centralised UDDI is a less robust structure and does not support a large number of web services. If the distributed environment is introduced into the UDDI, there will be a rapid increase in services with minimisation of resource consumption. Accordingly, mechanisms are needed for efficient selection of the appropriate instance of the web service in terms of factors like quality and performance. Distribution mechanisms, clustering and classification are necessary for efficient selection of the appropriate web service to the customer needs. In this paper, we propose a shared repository (ontology) which is produced by clustering of web services. This ontology can be exploited by the UDDI for publishing and discovering web services. A matching algorithm is also proposed to show how to perform this operation. A prototype tool has been developed to support experiments that have been carried out to evaluate and show the efficiency of our matching algorithm. We also introduce a comparative analysis to show the effectiveness of our approach compared to existing works.

Keywords: web service discovery; ontology; distributed architecture; classification; service registration.

DOI: 10.1504/IJAISC.2017.084586

International Journal of Artificial Intelligence and Soft Computing, 2017 Vol.6 No.2, pp.129 - 147

Received: 13 Jan 2016
Accepted: 26 Jan 2017

Published online: 15 Jun 2017 *

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