基于Drools规则引擎的物联网数据查询方法设计  

Internet of Things Data Query Method Based on Drools Rule Engine

作　　者：杜星熠 胡静[1] 蒋伟 宋铁成[1] DU Xing-yi;HU Jing;JIANG Wei;SONG Tie-cheng(School of Information Science and Engineering,Southeast University,Nanjing 210096,China)

机构地区：[1]东南大学信息科学与工程学院,江苏南京210096

出　　处：《测控技术》2022年第8期71-77,共7页Measurement & Control Technology

基　　金：国家重点研发计划项目(2020YFB1600104);江苏省重点研发计划(BE2020084-2)。

摘　　要：物联网(IoT)数据具有数据量大和实时性好的特点。通过复杂事件处理技术处理物联网数据时需要设置复杂的规则,但规则往往会随着业务的变化而变化。Drools规则引擎可以通过分离的配置文件设置规则,在不修改设备数据或管理平台代码的情况下,筛选到匹配规则的数据或事物。为解决DRL规则文件架构和决策表文件架构筛选数据产生的重复匹配的冗余问题,设计了一种修正数据库的数据查询方法。在不同数据量、不同规则数的查询环境下,对DRL规则文件架构、决策表文件架构和修正数据库架构进行了数据查询性能分析。实验结果表明:修正数据库架构在大数据量查询时时间损耗更少,可有效减少冗余。Internet of things(IoT) data has the characteristics of large amount of data and good real-time performance.Complex rules need to be set when processing IoT data through complex event processing technology, but the rules often change with the change of business.Drools rule engine can set rules through separate configuration files to filter data or things that match the rules without modifying device data or management platform code.In order to solve the redundancy problem of repeated matching caused by DRL rule file architecture and decision table file architecture, a data query method for modified database is designed.Under the query environment of different data volume and different rule number, the data query performances of DRL rule file architecture, decision table file architecture and modified database architecture are analyzed.The experimental results show that the modified database architecture can reduce the time loss and redundancy effectively when querying large data volume.

关 键 词：IOT Drools规则引擎 复杂事务管理 数据查询 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]