A quality-centric scheme for web service ranking using fuzzified QoS parameters

Abstract

Service composition, the process of combining already available basic services to provide a new, enhanced functionality, helps in serving diverse user requirements and promotes rapid application deployment. One of the premises for achieving service composition is to consider the quality of service parameters like availability, response times etc., of the constituent services, so that effective ranking can be obtained. However, based on user need, multiple criteria may need to be considered during QoS-based ranking, due to which it may be difficult to provide accurate and precise values with respect to a particular QoS parameter. In this paper, we address this problem by incorporating the theory of fuzzy logic using fuzzy variables. We propose a new scheme that focuses on computing the combined values of various QoS parameters, for enhancing web service recommendation. The proposed scheme has been applied to the real-world datasets, with encouraging results. � Springer Nature Singapore Pte Ltd. 2018.