QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
Efficient algorithms for Web services selection with end-to-end QoS constraints
ACM Transactions on the Web (TWEB)
Adaptive Service Composition in Flexible Processes
IEEE Transactions on Software Engineering
A discrete particle swarm optimization algorithm for the generalized traveling salesman problem
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Matching Strictly Dependent Global Constraints for Composite Web Services
ECOWS '07 Proceedings of the Fifth European Conference on Web Services
Matching independent global constraints for composite web services
Proceedings of the 17th international conference on World Wide Web
Model-Based Adaptation of Behavioral Mismatching Components
IEEE Transactions on Software Engineering
An Adaptive Service Selection Approach to Service Composition
ICWS '08 Proceedings of the 2008 IEEE International Conference on Web Services
QoS-Based service selection and ranking with trust and reputation management
OTM'05 Proceedings of the 2005 Confederated international conference on On the Move to Meaningful Internet Systems - Volume >Part I
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Under the service-oriented circumstances, developers can rapidly create applications through Web service composition. Owing to existing service selection methods having close relationship with the available service number, the efficiency inevitably decreases with the increase of available services. In the paper, a discrete Particle Swarm Optimization (DPSO) oriented to efficient service selection is designed according to Particle Swarm Optimization (PSO) idea. Furthermore, aiming at the practice service composition requirements, an algorithm used to resolve the dynamic service selection with multi-objective and quality of service (QoS) global optimal is presented based on DPSO and the theory of intelligent optimization of multi-objective PSO. Theoretical analysis and experimental results show that DPSO and multi-objective DPSO (MODPSO) are both feasible and efficient in the process of service selection.