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     Research Journal of Applied Sciences, Engineering and Technology


Web Service Discovery with Quality of Service (QoS) Parameters using Bayesian Belief Network

1A. Gnanasekar and 2R.M. Suresh
1Department of Computer Science and Engineering, R.M.D. Engineering College
2Sri Muthukumaran Institute of Technology, Anna University, Chennai 601206, India
Research Journal of Applied Sciences, Engineering and Technology  2014  22:2272-2281
http://dx.doi.org/10.19026/rjaset.8.1229  |  © The Author(s) 2014
Received: September ‎13, ‎2014  |  Accepted: October ‎12, 2014  |  Published: December 15, 2014

Abstract

The aim of this study is to present a novel approach which uses the belief net to intelligently infer the best and most relevant web service based on the available Quality of service parameters. Service Oriented Architecture (SOA) is the discovery of relevant Web Services for a specified task is a one of the key challenges. As Web services proliferate, there is a possibility of existing more than one service with same functionalities consequently; most of service discovery method will return several services which meet user given input and output. Finding the mainly relevant and best service is very crucial for the service consumers. In this situation, the non-functional Quality of Service (QoS) parameters present in the service description provided by the service provider play a major responsibility.

Keywords:

Bayesian belief network, , discovery, , quality of service parameters, , service oriented architecture, , web service,


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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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