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

被引：0

作者：

Yang B. ^{[1
,2
,3
]}

Guo H. ^{[2
]}

Feng J. ^{[2
]}

Li G. ^{[1
,2
,3
]}

Jin Z. ^{[4
,5
]}

机构：

[1] School of Information Science & Technology, Beijing Forestry University, Beijing

[2] School of Information Science & Technology, North China University of Technology, Beijing

[3] Engineering Research Center for Forestry Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing Forestry University, Beijing

[4] School of Computer Science, Peking University, Beijing

[5] Key Laboratory of High Confidence Software Technologies, Peking University, Ministry of Education, Beijing

来源：

Jisuanji Yanjiu yu Fazhan/Computer Research and Development | 2023年 / 60卷 / 03期

基金：

中国国家自然科学基金;

关键词：

conflict detection; intelligent system; Internet of things; rule conflict; rule formalization;

D O I：

10.7544/issn1000-1239.202110941

中图分类号：

学科分类号：

摘要：

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. © 2023 Science Press. All rights reserved.

引用

页码：592 / 605

页数：13

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