Research of proactive complex event processing method

Shao-feng GENG; Yong-heng WANG; Ren-fa LI; Jia ZHANG

doi:10.11959/j.issn.1000-436x.2016183

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Research of proactive complex event processing method

Papers | 更新时间：2024-06-05

- Research of proactive complex event processing method
- Journal on Communications Vol. 37, Issue 9, Pages: 111-120(2016)
- 作者机构：
  
  1. 湖南大学信息科学与工程学院，湖南长沙 410082
  2. 集美大学计算机工程学院，福建厦门 361021
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61173036);The National Natural Science Foundation of China(61371116);Foundation of Fujian Educational Committee(JA14186)
- DOI：10.11959/j.issn.1000-436x.2016183
  CLC： TP391
- Online First：2016-09，
  
  Published：25 September 2016
- 稿件说明：
移动端阅览
Shao-feng GENG, Yong-heng WANG, Ren-fa LI, et al. Research of proactive complex event processing method[J]. Journal on Communications, 2016, 37(9): 111-120.
DOI：

Shao-feng GENG, Yong-heng WANG, Ren-fa LI, et al. Research of proactive complex event processing method[J]. Journal on Communications, 2016, 37(9): 111-120. DOI： 10.11959/j.issn.1000-436x.2016183.

摘要

在CPS的应用背景下，对传感器和控制设备产生的不确定性事件流进行分析和处理得出高层事件，然后在此基础上引入适应性动态贝叶斯网络和并行马尔可夫决策过程模型来支持主动式的复杂事件处理。针对大型CPS中马尔可夫决策过程存在的状态数量巨大的问题，引入状态划分和报酬分解的方法来进行并行优化。在模拟交通网络的环境中，实验结果显示所提方法能有效地处理事件流，并具有良好的可扩展性。

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.

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Keywords

references

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