WEB SERVICE SELECTION ALGORITHM BASED ON PRINCIPAL COMPONENT ANALYSIS

Existing Web service selection approaches usually assume that preferences of users have been provided in a quantitative form by users. However, due to the subjectivity and vagueness of preferences, it may be impractical for users to specify quantitative and exact preferences. Moreover, due to that Quality of Service (QoS) attributes are often interrelated, existing Web service selection approaches which employ weighted summation of QoS attribute values to compute the overall QoS of Web services may produce inaccurate results, since they do not take correlations among QoS attributes into account. To resolve these problems, a Web service selection framework considering user's preference priority is proposed, which incorporates a searching mechanism with QoS range setting to identify services satisfying the user's QoS constraints. With the identified service candidates, based on the idea of Principal Component Analysis (PCA), an algorithm of Web service selection named PCA-WSS (Web Service Selection based on PCA) is proposed, which can eliminate the correlations among QoS attributes and compute the overall QoS of Web services accurately. After computing the overall QoS for each service, the algorithm ranks the Web service candidates based on their overall QoS and recommends services with top QoS values to users. Finally, the effectiveness and feasibility of our approach are validated by experiments, i.e. the selected Web service by our approach is given high average evaluation than other ones by users and the time cost of PCA-WSS algorithm is not affected acutely by the number of service candidates.

Toward a More Accurate Web Service Selection Using Modified Interval DEA Models with Undesirable Outputs

With the growing number of Web services on the internet,there is a challenge to select the best Web service which can offer more quality-of-service(QoS)values at the lowest price.Another challenge is the uncertainty of QoS values over time due to the unpredictable nature of the internet.In this paper,we modify the interval data envelopment analysis(DEA)models[Wang,Greatbanks and Yang(2005)]for QoS-aware Web service selection considering the uncertainty of QoS attributes in the presence of desirable and undesirable factors.We conduct a set of experiments using a synthesized dataset to show the capabilities of the proposed models.The experimental results show that the correlation between the proposed models and the interval DEA models is significant.Also,the proposed models provide almost robust results and represent more stable behavior than the interval DEA models against QoS variations.Finally,we demonstrate the usefulness of the proposed models for QoS-aware Web service composition.Experimental results indicate that the proposed models significantly improve the fitness of the resultant compositions when they filter out unsatisfactory candidate services for each abstract service in the preprocessing phase.These models help users to select the best possible cloud service considering the dynamic internet environment and they help service providers to improve their Web services in the market.

FEWSS-FRAMEWORK TO EVALUATE THE SERVICE SUITABILITY AND PRIVACY IN A DISTRIBUTED WEB SERVICE ENVIRONMENT

This paper focuses on addressing the problem of web service monitoring by evaluating its suitability and privacy in a distributed web service environment(DWS).The need for web services monitoring and evaluation is necessary because the quantity and quality of retrieved web services generally does not fulfill the demands or requirements of the web service requesters.In the literature,many authors proposed suitable solutions for checking the quality of web service in an ad hoc scenario but there is no available testbed for this purpose.In this work,it is proposed to develop a framework as a testbed for evaluating the web service for its suitability and privacy.In order to verify,the retrieved web services fulfill the demands and requirements of the requester in a DWS environment.The Framework to Evaluate the Web Service Suitability(FEWSS)supports service providers in modeling the services with testbed and to design service behavior to comply the service suitability.It generates run-time instances of web services,client’s requests,service registries and other entities in order to emulate realistic SOA environments.By generating a real testbed,our approach assists in runtime test for provider system/services.Particular focus has been put on the privacy policy extensibility to allow the service providers and users in a complex environment.FEWSS also provides an intuitive interface for testing all services under SOA control.