Combining QoS-based Service Selection with Performance Prediction

Authors:
Zhengdong Gao;Gengfeng Wu
Affiliations:
Shanghai University;Shanghai University
Venue:
ICEBE '05 Proceedings of the IEEE International Conference on e-Business Engineering
Year:
2005

Citing 0
Cited 7

Learning-based trust model for optimization of selecting web services

APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
An empirical comparison of methods to support QoS-aware service selection

Proceedings of the 2nd International Workshop on Principles of Engineering Service-Oriented Systems
A QOS enhanced framework and trust model for effective web services selection

Journal of Web Engineering
A QOS enhanced framework and trust model for effective web services selection

Journal of Web Engineering
Towards automated service quality prediction for development of enterprise mashups

Proceedings of the 5th International Workshop on Web APIs and Service Mashups
A novel approach for service performance analysis and forecast

Journal of Web Engineering
ServBGP: BGP-inspired autonomic service routing for multi-provider collaborative architectures in the cloud

Future Generation Computer Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Currently, much efforts have being focused on dynamic, personalized QoS-based service selection, however, current QoS models are generally composed of static QoS parameters and haven't taken the dynamic nature of service performance into consideration. In our framework, we extend existing QoS model by adding new attributes that reflect performance of services and rely on ANN to provide client dynamic, on demand service performance prediction. Through this way, a client may be more capable of finding the best service based both on his/her preferences and on the service performance estimation.