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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.
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Basic Information:
DOI：10.13705/j.issn.1671-6841.2022317
China Classification Code:TN929.5;TP391.44
Citation Information:
[1]WANG Xiaoxuan,WANG Guiling.An IoT-aware Business Micro-process Modeling Method[J].Journal of Zhengzhou University(Natural Science Edition),2024,56(02):26-33.DOI:10.13705/j.issn.1671-6841.2022317.
Fund Information:
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)
2023-09-13
2023-09-13
2023-09-13