An Extensible and Personalized Approach to QoS-enabled Service Discovery

We present an extensible and customizable framework for the autonomous discovery of Semantic Web services based on their QoS properties. Using semantic technologies, users can specify the QoS matching model and customize the ranking of services flexibly according to their preferences. The formal modeling of the discovery process as a query execution plan facilitates the introduction of different discovery algorithms and the automatic generation of parallelized matchmaking evaluations. This enables adapting our approach to unpredictable arrival rates of user queries and scales up to high numbers of published service descriptions.