Abstract
ABSTRACT In this paper, a multilayered clustering framework is proposed to build a service portfolio to select web services of choice. It is important for every service provider to create a service portfolio in order to facilitate the service selection process for someone to obtain the desired service in the absence of public UDDI registries. To address this problem, a multilayered clustering approach applied on a variety of data pertaining to web services in order to filter and group the services of a similar kind which in turn will improve the leniency in the process of service selection is used. The advantages of the layer approach are reduced search space, combination of incremental learning and competitive learning strategies, reduced computational labour, scalability, robustness and fault tolerance. The results are subjected to cluster analysis to verify their degree of compactness and isolation and appropriate evaluation indices are used. The results were found passable with an improved degree of similarity.
Highlights
A Service provider in general has to do the following to put a service available for use in a conventional approach
As public registries are closed it becomes essential for service providers to make all the web service descriptions that are published available in order to choose or search a web service preferably in a proprietary portal
Non-Functional data (QoS parameters) Quality of Services (QoS) (Quality of Service) attributes of a web service can be understood as the capacity of a web service to act in response to expected invocations
Summary
A Service provider in general has to do the following to put a service available for use in a conventional approach. The discovery process is made successful defending on the maturity and capability of the matching process in order to make the search process easier an arrangement and organization of services grouping them based on certain relevancy factors is an indispensable factor. In this context two issues are of primary concern, One, a procedure for categorization of services through efficient clustering techniques in order to facilitate any match making process to fetch the right service based on the requirements.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
