Journal on Communications ›› 2016, Vol. 37 ›› Issue (9): 111-120.doi: 10.11959/j.issn.1000-436x.2016183

• Papers • Previous Articles     Next Articles

Research of proactive complex event processing method

Shao-feng GENG1,2,Yong-heng WANG1,Ren-fa LI1,Jia ZHANG2   

  1. 1 College of Information Science and Engineering,Hunan University,Changsha 410082,China
    2 College of Computer Engineering,Jimei University,Xiamen 361021,China
  • Online:2016-09-25 Published:2016-09-28
  • Supported by:
    The National Natural Science Foundation of China;The National Natural Science Foundation of China;Foundation of Fujian Educational Committee

Abstract:

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.

Key words: CPS, big data, complex event processing, Markov decision process

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