BUILDING REPUTATION FOR SERVICE-ORIENTED AMI: MODELING, ALGORITHMS, AND ANALYSIS

Service reputation is a key factor for service selection and service composition inService-Oriented Ambient Intelligence systems. Hence, service reputation computing should fullyreflect the feature of multi-rating fusion and the utility value dynamic attenuation characters of therating. The paper combines D-S evidence theory with dynamic attenuation and puts forward aservice reputation computing algorithm based on multi-rating fusion, which is adapted to theAmbient Intelligence systems. First, a layered computing model of the service reputation is given.Then, a mechanism of dynamic attenuation based on time windows, an objective rating andadvertisement honesty rating of service, and a user credibility computing algorithm are presented.Afterward, the rating information is combined with the D-S evidence theory to raise anaggregation algorithm of the service general reputation for the Ambient Intelligence environments.Finally, a prototype test is carried out to verify the effectiveness and availability of the modeltogether with the algorithms.