Trust Evaluation for Service Composition in Cloud Manufacturing Using GRU and Association Analysis

Abstract

Service composition enables the flexible and agile collaboration of multiple services to complete personalized manufacturing tasks in cloud manufacturing. Compared with traditional manufacturing mode and cloud computing, trust problems become more serious and crucial in cloud manufacturing because of the nontransparency and short-term cooperation mode. A trust evaluation method for service composition in cloud manufacturing is proposed in this article. To quantitatively calculate the trust, a trust evaluation index system is established that comprehensively considers the influencing factors in the production, transaction, and collaboration processes of cloud manufacturing services. The trust value is synthesized based on all index values using the criteria importance through intercriteria correlation method. To extract the temporal information in historical trust data, a time-aware predictive trust evaluation method based on gated recurrent unit is proposed to learn the changing pattern of trust value over time. The trust data are trained together with their timestamps to predict the trust in the scheduled transaction time. The correlation between services in service composition is modeled to mine the correlation information by association analysis. The trust of service composition depends on the trust values of all component services and the correlations between them. The experiments demonstrate the effectiveness of the proposed method through case studies and performance comparisons with other state-of-art methods.