یک رویکرد پیشگیرانه بر اساس پیش بینی قابلیت اطمینان آنلاین برای سازگاری سیستم های سرویس گرا

Service computing is an emerging technology in System of Systems Engineering (SoS Engineering or SoSE), which regards System as a Service (i.e. SaaS), and aims to construct a robust and value-added complex system by outsourcing external component systems through service composition technology. A service-oriented SoS runs under a dynamic and uncertain environment. To successfully deploy SoS’s run-time quality assurance, online reliability time series prediction, which aims to predict the reliability in near future for a service-oriented SoS,arises as a grand challenge in SoS research. In this paper, we tackle the prediction challenge by exploiting two novel prediction models. We adopt motifs-based Dynamic Bayesian Networks (or m_DBNs) model to perform one-step-ahead time series prediction, and propose a multi-steps trajectories DBNs (or multi_DBNs) model to further revise the future reliability prediction. Finally, a proactive adaption strategy is achieved based on the reliability prediction results. Extensive experiments conducted on real-world Web services demonstrate that our models outperform other well-known approaches consistently.