Abstract. Ranking and optimization of web service compositions are some of the most interesting challenges at present. Since web services can be enhanced with formal semantic descriptions, forming the "semantic web services", it becomes conceivable to exploit the quality of semantic links between services (of any composition) as one of the optimization criteria. For this we propose to use the semantic similarities between output and input parameters of web services. Coupling this with other criteria such as quality of service (QoS) allow us to rank and optimize compositions achieving the same goal. Here we suggest an innovative and extensible optimization model designed to balance semantic fit (or functional quality) with non-functional QoS metrics. To allow the use of this model in the context of a large number of services as foreseen by the strategic EC-funded project SOA4All we propose and test the use of Genetic Algorithms.
REF proposed a Web Service Composition extensible optimization model designed to balance semantic similarities and quality of service QoS using Genetic Algorithms.
Optimizing QoS-Aware Semantic Web Service Composition
International Semantic Web Conference
Computer Science