Research on rule engine optimization algorithm in internet of things teaching platform

JianZhong Li, Qiang Wan, ZhiQiang Zhang
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Abstract

The rule engine is an important part of the industry-education integrated Internet of Things teaching platform, and it is the basis for realizing the dynamic configuration of business rules in the practical teaching function. Combined with the data characteristics of the Internet of Things application scenario, this paper proposes a rule engine optimization algorithm based on Rete, and designs a pre-sorting algorithm based on rule frequency, which pre-sorts the order of nodes according to the frequency of use of rule patterns, with priority Match frequently used patterns, increases the sharing rate of nodes, and reduce the memory usage of the inference network. Through experimental simulation, the improved algorithm is verified, and the experimental results prove the effectiveness of the algorithm.
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物联网教学平台中的规则引擎优化算法研究
规则引擎是产教融合物联网教学平台的重要组成部分,是实现实践教学功能中业务规则动态配置的基础。结合物联网应用场景的数据特点,本文提出了基于Rete的规则引擎优化算法,设计了基于规则使用频率的预排序算法,根据规则模式的使用频率预排序节点顺序,优先匹配常用模式,提高节点共享率,降低推理网络的内存占用。通过实验仿真,验证了改进后的算法,实验结果证明了算法的有效性。
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