Back to Search
Start Over
Policy conflict detection approach for decision-making in intelligent industrial Internet of Things.
- Source :
-
Computers & Electrical Engineering . May2023, Vol. 108, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
-
Abstract
- • The rule conflicts are subdivided into seven categories. • Different rule conflicts are formally expressed so that the detection of rows can be automated to improve the accuracy. • Designs and implementation of prototype system for rule conflict detection. • F1 value of proposed rule conflict detection in the IIOT system is better. Improving Industrial Internet of Things (IIOT), device flexibility and lowering maintenance costs are significant problems. However, as the scale of the Intelligent Industrial Internet of Things (IIIOTs) system expands, the interactions between the rules get more sophisticated, potentially leading to rule discrepancies. The algorithm for Formal Rule Conflict Detection (FRCD) is created, and a thorough explanation of the procedure is given in this paper. Two IIIOT systems were used in experiments and the results were compared with three existing standard IIIOT rule conflict detection techniques. They include policy conflict detection systems based on Web semantics (Semantic Web-Based Policy Interaction Detection with Rules, (SPIDER)), conflict detection methods based on Users, Triggers, Environment entities, and Actuators (UTEA), and semiformal conflict detection methods (Identifying Requirements Interactions using Semiformal (IRIS)). The experimental results show that the FRCD rule conflict detection method is superior. [Display omitted] [ABSTRACT FROM AUTHOR]
- Subjects :
- *INTERNET of things
*MAINTENANCE costs
*DECISION making
*SEMANTIC Web
Subjects
Details
- Language :
- English
- ISSN :
- 00457906
- Volume :
- 108
- Database :
- Academic Search Index
- Journal :
- Computers & Electrical Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 163995585
- Full Text :
- https://doi.org/10.1016/j.compeleceng.2023.108671