On the Use of Fuzzy Dominance for Computing Service Skyline Based on QoS

Abstract

Nowadays, the exploding number of functionally similar Web services has led to a new challenge of selecting the most relevant services using quality of service (QoS) aspects. Traditionally, the relevance of a service is determined by computing an overall score that aggregates individual QoS values. Users are required to assign weights to QoS attributes. This is a rather demanding task and an imprecise specification of the weights could result in missing some user desired services. Recent approaches focus on computing service skyline over a set of QoS aspects. This can completely free users from assigning weights to QoS attributes. However, two main drawbacks characterize such approaches. First, the service skyline often privileges services with a bad compromise between different QoS attributes. Second, as the size of the service skyline may be quite large, users will be overwhelmed during the service selection process. In this paper, we introduce a new concept, called alpha-dominant service skyline, to address the above issues and we develop a suitable algorithm for computing it efficiently. Experimental evaluation conducted on synthetically generated datasets, demonstrates both the effectiveness of the introduced concept and the efficiency of the proposed algorithm.