QoS-based service optimization using differential evolution
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Adaptive MOEA/D for QoS-based web service composition
EvoCOP'13 Proceedings of the 13th European conference on Evolutionary Computation in Combinatorial Optimization
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At present, the Service composition has been a popular research. It is unrealistic to manually analyze and compose the existing services appearing with tremendous growth recently. So, many applications and research about composite services emphasize on semi-automatic mode. In semi-automatic service composition, developers should construct the process model according to concrete application requirement, and then the instance services are bound automatically for every abstract task and make the composite service with optimal performance. The paper presents independent global constrains-aware Web service composition method based on extended Color Petri net (eCPN) and genetic algorithm (GA). Firstly, an eCPN modeling methods which can describe multi-attribute multi-constraint relations and associate relation between component services is proposed. Secondly, combining with the properties of eCPN, GA is used to search a legal firing sequence in the eCPN model, and the composite service corresponding to the legal firing sequence. Using legal firing sequences of the Petri net makes the service composition locating space based on GA shrink greatly. Theoretical analysis and experimental results indicate that this method owns both lower computation cost and higher success ratio of service composition.