A Novel Online Reliability Prediction Approach for Service-Oriented Systems

Service composition is an emerging technology in System of Systems Engineering (SoS Engineering or SoSE), which aims to construct a robust and value-added complex system by outsourcing external component systems. A serviceoriented SoS runs under a dynamic and uncertain environment. To assure the overall Quality of Service (QoS), online reliability time series prediction, which aims to predict the reliability in near future for service-oriented SoS arises as a grand challenge in SoS research. In this paper, we tackle the prediction challenge by exploiting two Markov independence assumptions resulted from the special system dynamics of a SoS environment. A novel motifs-based Dynamic Bayesian Networks model is proposed that supports the independence assumptions. Experimental results conducted on real Web services demonstrate the effectiveness of our approach.