Rank Aggregation for QoS-Aware Web Service Selection and Composition

Service Composition is an essential part of Service Oriented Architectures (SOA). The number of available alternatives for web services offering similar functional characteristics opens opportunities to maximise compositions based on criteria embedded into the Quality of Service (QoS). These non-functional criteria may be numerous and diverse, and arise from various constraints, making composition an optimal information fusion problem. A number of solutions have been offered to resolve the selection problem for web service composition, essentially relying on exploiting and combining absolute performance values for measuring multi-dimensional QoS. In this paper, we investigate the use of Rank Aggregation methods for performing adequate information fusion for web service selection in view of composition. Our goal is to take advantage of these methods working on ranks rather than on the direct values for inferring global QoS. We formalise our approach and demonstrate its validity via an empirical study. We further evaluate our approach on publicly available real data gathered from actual web service characteristics.