A model for web services discovery with QoS
ACM SIGecom Exchanges
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
Context for Personalized Web Services
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences - Volume 07
The Applicability of Adaptive Control Theory to QoS Design: Limitations and Solutions
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 15 - Volume 16
Self-healing web service compositions
Proceedings of the 27th international conference on Software engineering
Composing Business Processes with Partial Observable Problem Space in Web Services Environments
ICWS '06 Proceedings of the IEEE International Conference on Web Services
Reliable QoS monitoring based on client feedback
Proceedings of the 16th international conference on World Wide Web
Speeding up adaptation of web service compositions using expiration times
Proceedings of the 16th international conference on World Wide Web
Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering
Systematic Approach for QoS Estimation of Web Services
Proceedings of International Conference on Information Integration and Web-based Applications & Services
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In recent years, many QoS-based web service selection methods have been proposed. However, as QoS changes dynamically, the atomic services of a composite web service could be replaced with other ones that have better quality. The performance of a composite web service will be decreased if this replacement happens frequently in runtime. Predicting the change of QoS accurately in select phase can effectively reduce this web services “thrash”. In this paper, we propose a web service selection algorithm GFS (Goodness-Fit Selection algorithm) based on QoS prediction mechanism in dynamic environments. We use structural equation to model the QoS measurement of web services. By taking the advantage of the prediction mechanism of structural equation model, we can quantitatively predict the change of quality of service dynamically. Optimal web service is selected based on the predicted results. Simulation results show that in dynamic environments, GFS provides higher selection accuracy than previous selection methods.