Efficient Microservices Discovery and Selection Based on QoS Ontology a Data Mining Approach
Neha Singhal1, Usha Sakthivel2, Pethuru Raj3
1Neha Singhal, Department of Information Science and Engineering, Rajarajeswari College of Engineering, Bangalore (Karnataka) India.
2Usha Sakthivel, Department of Computer science and Engineering, Rajarajeswari College of Engineering Bangalore (Karnataka) India.
3Pethuru Raj, Reliance Jio Info Comm. Ltd (RJIL), SARGOD Imperial, 23, Residency Road Bangalore (Karnataka) India.
Manuscript received on 01 May 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 1689-1695 | Volume-8 Issue-7, May 2019 | Retrieval Number: G6376058719/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Microservices is emerging as a revolutionary and modern solution in the recent software era. Microservices is also based on web services but it could be implemented as an independent feature to perform a specific task with its own database. In the growing field of e-commerce, when user aim to find microservice meeting to their dynamic business requirement is becoming a big challenge and emerging as a problem. This problem occurs, because the number of related service is increasing day by day in the repository and selection of the appropriate and quality service is a main challenge. In order to solve this problem, in this paper we propose a QoS ontology semantic annotation approach with reducing the difficulty of appropriate service discovery and selection as per user dynamic requirement using association rules and K-means clustering techniques.
Keyword: QoS, Ontology, Microservices, K-Means, Association Rules.
Scope of the Article: Data Mining.