IWSS INTELLIGENT WEB SERVICE SELECTION FOR SERVICEORIENTED

Abstract

The world of web services is gigantic and the demand of web services is increasing day by day because of functionalities provided by them. With increase in number of available web services the task of discovery and selection of web services is becoming exigent when there is large number of services providing the similar functionality. Mainstream approaches for WS selection rely on functional description of the service as published by the service provider. Moreover, there is no provision for adapting the service selection behavior by taking into account user’s run-time experience with the service. The framework presented in this paper combines functional parameters of published WS with accumulated store of previous users’ Quality of Experience (QoE) in a Case Based Reasoning (CBR) system for precise selection of best WS for a user query. Proposed framework is also incorporating the users’ preferences with service request parameters and collects users’ feedback to select the most appropriate service for a user’s request. CBR remembers service selection made in presence of functional and QoE parameters to guide decision-making when faced with similar situation in future Experimental results show that the proposed approach gives much more precise results than naive approaches. It provides the optimal service to users with ease of usage.