The ant colony Optimization Algorithm for web services composition on Preference Ontology

The Optimization Algorithm for Web Services Composition on Preference Ontology (OAWSCP) is put forward. OAWSCP, which makes some improvements on primary ACO (Ant Colony Optimization), builds simulation model based on services composition, and sets multiple pheromones and pheromone weights to denote the preference to different properties of a service. The algorithm can also simulate the instability of the flow of services composition, and react according to the flow change of the services composition. The algorithm can also detect if the optimizing is converging to local optimization findings, and in this case the algorithm can take measures to change its direction, and as a result reduce the probability of the algorithm to converge to local optimization findings. In order to verify the feasibility of the algorithm, the paper also builds simulation application system. The result of the performance test proves that the algorithm is more effective than primary ACO.