The Self-Serv Environment for Web Services Composition
IEEE Internet Computing
Ant Colony Optimization
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
Quality Driven Web Services Selection
ICEBE '05 Proceedings of the IEEE International Conference on e-Business Engineering
Efficient algorithms for Web services selection with end-to-end QoS constraints
ACM Transactions on the Web (TWEB)
On Solving QoS-Aware Service Selection Problem with Service Composition
GCC '08 Proceedings of the 2008 Seventh International Conference on Grid and Cooperative Computing
A QoS-Based Web Services Selection Method for Dynamic Web Service Composition
ETCS '09 Proceedings of the 2009 First International Workshop on Education Technology and Computer Science - Volume 03
IFITA '09 Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01
Optimizing QoS-Aware Semantic Web Service Composition
ISWC '09 Proceedings of the 8th International Semantic Web Conference
The Research of Web Service Selection Based on the Ant Colony Algorithm
AICI '10 Proceedings of the 2010 International Conference on Artificial Intelligence and Computational Intelligence - Volume 03
Solving the attribute reduction problem with ant colony optimization
Transactions on rough sets XIII
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With the increasingly emerging Web services, QoS-aware service selection is an active research area on Web services composition. It is a complex combinatorial optimization problem, which solves how to find a best composition plan that maximizes user's QoS requirement. In this paper a QoS-aware Web services selection model is proposed using AND/OR Graph after discussing the QoS critera. The model is not only capable of dealing with sequence relations and fork relations, but also capable of dealing with parallel relations between services, and the multi-objective constraint function is defined to meet the QoS. Furthermore, a novel service selection algorithm is proposed based on the ant colony optimization. Finally, the algorithm is tested for the performance.