Service selection based on personalized preference and trade-offs among QoS factors and price

With the number of services with similar functionalities rising, service users place more emphasis on non-functional attributes of services such as quality of service (QoS) and price during service selection. However, previous QoS-driven service selection methods seldom consider relationships among non-functional requirements and do not allow explicit specification of personalized preferences and trade-offs from user perspectives to select services. In addition, most of them use weighted summation functions to aggregate multiple QoS factors to rank services for selection. This paper presents a novel service selection method, in which users can represent their non-functional requirements using linguistic terms and use their personalized trade-off strategies for service selection. The method employs fuzzy propositions in conjunction with QoS and price information to compute satisfaction degree of individual non-functional requirements. Based on the personalized trade-off strategy of a user, it then computes the overall satisfaction degree using fuzzy connective operators. The overall satisfaction degree of services is then used to rank services with equivalent functionalities and top-ranked services are recommended. An application example is presented to show the method's effectiveness.