A Rule Conflict Detection Approach for Intelligent System of Internet of Things

Yang Bo; Guo Haoran; Feng Junhui; Li Ge; Jin Zhi

doi:10.7544/issn1000-1239.202110941

Journal of Computer Research and Development > 2023 > 60(3): 592-605. > DOI: 10.7544/issn1000-1239.202110941

Yang Bo, Guo Haoran, Feng Junhui, Li Ge, Jin Zhi. A Rule Conflict Detection Approach for Intelligent System of Internet of Things[J]. Journal of Computer Research and Development, 2023, 60(3): 592-605. DOI: 10.7544/issn1000-1239.202110941

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A Rule Conflict Detection Approach for Intelligent System of Internet of Things

Yang Bo^{1, 2, 3,},
Guo Haoran²,
Feng Junhui²,
Li Ge^{4, 5,},
Jin Zhi^{4, 5, ,}

1.
School of Information Science & Technology, Beijing Forestry University, Beijing 100083
2.
School of Information Science & Technology, North China University of Technology, Beijing 100144
3.
Engineering Research Center for Forestry Oriented Intelligent Information Processing, National Forestry and Grassland Administration (Beijing Forestry University), Beijing 100083
4.
School of Computer Science, Peking University, Beijing 100871
5.
Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, Beijing 100871

Funds: This work was supported by the Fundamental Research Funds for the Central Universities (BLX202003), the National Natural Science Foundation of China (62072007, 62192733, 61832009,62192730, 61772078, 61502011), and the Focus Tracking Project of Beijing Forestry University (BLRD202124).

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Received Date: September 14, 2021
Revised Date: June 18, 2022
Available Online: February 26, 2023

Graphical Abstract

Abstract

Abstract

The core of the Internet of things (IoT) system architecture is the logic controller. The logic controller uses rules to control the business logic, which reduces the development and maintenance costs of the IoT system and improves the flexibility of the IoT devices. As the scale of the IoT system expands, the relationship between the rules becomes complicated. This may cause rule conflicts. In response to this problem, some researchers have proposed some detection methods for rule conflicts. However, the existing rule conflict detection methods still have some problems, such as incomplete analysis of rule conflict types and low accuracy of detection results. For these reasons, a formal rule conflict detection (FRCD) method for the control logic of the IoT intelligent system is proposed. This method formalizes the structure of rules, and defines rules as a combination of control subjects, actions, trigger conditions, and symbols. Then according to the influence of the rules on the system and the structural characteristics of the rules, 7 types of rule conflicts are summarized. Finally, an algorithm for rule conflict detection is designed, and the detailed process of rule conflict detection is introduced. We carry out experiments on two IoT systems and compare them with three typical IoT rule conflict detection methods. These three methods are the formal rule model conflict detection method based user, triggers, environment entities, and actuators (UTEA), semantic web-based policy interaction detection with rules (SPIDER), identifying requirements interactions using semiformal (IRIS). The experimental results show that the formal rule conflict detection method in this paper is more effective.
- Internet of things,
- intelligent system,
- rule conflict,
- conflict detection,
- rule formalization

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References (35)

References

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