Research of proactive complex event processing method - Shao-feng GENG; Yong-heng WANG; Ren-fa LI; Jia ZHANG (Tongxin xuebao)
Based on the preliminary analysis results of the indeterminate event stream that generated by the sensors and control purpose equipment of CPS,the adaptive dynamic Bayesian network and parallel Markov decision process model were used to support the proactive complex event processing.In order to resolve the vast state space issue of Markov decision process for large CPS,states partition and reward decomposition methods were proposed to parallel the decision making process.The experimental result based on the simulation of traffic network shows that proposed method can process event stream effectively and has favorable scalability.