Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Adaptive and Dynamic Service Composition in eFlow
CAiSE '00 Proceedings of the 12th International Conference on Advanced Information Systems Engineering
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
AO4BPEL: An Aspect-oriented Extension to BPEL
World Wide Web
A survey on web services composition
International Journal of Web and Grid Services
Event-Driven Quality of Service Prediction
ICSOC '08 Proceedings of the 6th International Conference on Service-Oriented Computing
Combining global optimization with local selection for efficient QoS-aware service composition
Proceedings of the 18th international conference on World wide web
An End-to-End Approach for QoS-Aware Service Composition
EDOC '09 Proceedings of the 2009 IEEE International Enterprise Distributed Object Computing Conference (edoc 2009)
Monitoring, Prediction and Prevention of SLA Violations in Composite Services
ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
Runtime prediction of service level agreement violations for composite services
ICSOC/ServiceWave'09 Proceedings of the 2009 international conference on Service-oriented computing
Adaptation of service-based applications based on process quality factor analysis
ICSOC/ServiceWave'09 Proceedings of the 2009 international conference on Service-oriented computing
Parameterized BPEL processes: concepts and implementation
BPM'06 Proceedings of the 4th international conference on Business Process Management
ESOCC'12 Proceedings of the First European conference on Service-Oriented and Cloud Computing
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Existing research work considers runtime adaptation of service compositions as a viable tool to prevent violations of service level agreements. In previous work we have formalized the optimization problem of identifying the most suitable adaptations to prevent a predicted set of violations, and presented suitable algorithms to solve this problem. Here, we introduce the idea of stepwise optimization as a solution to the problem of how to deal with situations when the optimization result is not available in time, i.e., when decisions need to be taken before the optimization problem can be fully solved.