摘要
基于物联大数据赋能的业务流程能够更快更准地感知物理世界并及时做出响应的需求突现,提出一种物联网(Internet of Things,IoT)感知的业务微流程建模方法。首先,以单个IoT对象为中心建模,融合MAPE-K(monitor,analysis,plan,execution and knowledge base,MAPE-K)模型思想,将IoT对象实例生命周期的行为状态与微流程实例状态一一映射,实现对单个IoT对象的环形自动监控和调节;其次,基于从IoT传感设备获取的数据,定义基于SASE+语言的业务规则,提取对业务流程有意义的业务事件,避免了无关事件对宏流程的干扰;最后,通过设计一个微流程建模工具原型系统,结合真实案例分析,验证了提出建模方法的有效性,实现了业务流程与IoT实时流式感知数据的结合,并显著减少了宏流程需要处理的业务事件数量。
A method of modeling IoT-aware business micro-processes was proposed,which could empower business processes to perceive the physical world faster and more accurately,and respond to emerging demands in a timely manner based on IoT big data.Firstly,a single IoT object was modeled as the center,and the MAPE-K model was integrated to map the behavioral states of IoT object instances in the life-cycle to the micro-process instance states,achieving automatic monitoring and regulation of a single IoT object in a circular manner.Secondly,based on the data obtained from IoT sensing devices,business rules were defined by using SASE+language,and meaningful business events relevant to the macro-process were extracted to avoid interference from irrelevant events.Finally,a micro-process modeling tool prototype system was designed,and the proposed modeling method was validated through real case analysis,realizing the integration of business processes and real-time stream sensing data from IoT,and significantly reducing the number of business events that the macro-process needs to process.
作者
王潇璇
王桂玲
WANG Xiaoxuan;WANG Guiling(School of Information,North China University of Technology,Beijing 100144,China;Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data,Beijing 100144,China)
出处
《郑州大学学报（理学版）》
CAS
北大核心
2024年第2期26-33,共8页
Journal of Zhengzhou University:Natural Science Edition
基金
国家自然科学基金国际(地区)合作与交流项目(62061136006)
国家自然科学基金重点项目(61832004)。
关键词
IoT流式感知数据
业务规则
环形自动监控调节
微流程
IoT streaming sensor data
business rules
circular automatic monitoring and regulation
micro-processes
