Semantic Discovery and Selection: A QoS-Aware, Hybrid Model

Abstract

Most Semantic Web Services discovery ap- proaches are based on Description Logics, allowing a limited expressiveness when describing Quality-of-Service preferences. Furthermore, DLs is not suited to perform se- lection tasks, because these are modeled as optimization problems. In this work, we present a hybrid discovery and selection model for Semantic Web Services that takes care of QOS preferences. Our approach splits the whole process into two stages, using the most suited engine in each one, depending on its search nature. In order to perform QOS- aware discovery and selection, user preferences have to be semantically described as the rest of the service description. Our model provides an ontology for user preferences, so in- stances can be transformed into optimization problems that can be solved by using the most suited engine.