QoS-aware web services selection with intuitionistic fuzzy set under consumer's vague perception

Appropriate application of service selection based on QoS-aware can bring great benefits to service consumers, as it is able to reduce redundancy in search. It also generates advantages for service providers who deliver valuable services. However, non-functional QoS attributes are not easy to measure due to their complexity and the involvement of consumer's fuzzy perceptions of QoS. In this paper, a new decision model under vague information is proposed. It extends Max-Min-Max composition of intuitionistic fuzzy sets (IFS) for selection of web services. Furthermore, an improved fuzzy ranking index is proposed to alleviate the bias of existing approaches. The index aggregates both concord and discord degrees of the decision maker's satisfaction in order to analyze the synthetic satisfaction degree for web services. In addition, an example of QoS-aware web services selection is illustrated to demonstrate the proposed approach. Finally, the proposed method is verified by a sensitivity analysis.

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