{"title":"面向场景感知和边缘决策的领域建模","authors":"Haoran Shi, Shijun Liu, Li Pan","doi":"10.1109/EDGE60047.2023.00028","DOIUrl":null,"url":null,"abstract":"The introduction of numerous edge computing nodes allows application systems to sense and make decisions in real-time but also brings new challenges. The diversity of application scenarios and the complexity of application processes can be effectively addressed through modeling. This paper proposes a modeling approach for manufacturing scenario sensing and edge decision-making. Firstly, an abstract meta-model (SMM) is defined, which provides a unified description of the resources and processes in the scenario and the interaction between the scenario and the edge. Based on the meta-model, an application scenario model (ASM) can be constructed for a specific scenario to support edge data feedback and decision-making for abnormal events. In addition, the model is constructed in a scenario modeling tool and validated in a simulated manufacturing production line, that is, whether the models can provide effective support for decision-making of abnormal events. The results demonstrate that mapping normalized models into codes at the edge computing nodes can improve the accuracy and real-time performance of decision-making.","PeriodicalId":369407,"journal":{"name":"2023 IEEE International Conference on Edge Computing and Communications (EDGE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Domain modeling for scenario sensing and edge decision-making\",\"authors\":\"Haoran Shi, Shijun Liu, Li Pan\",\"doi\":\"10.1109/EDGE60047.2023.00028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The introduction of numerous edge computing nodes allows application systems to sense and make decisions in real-time but also brings new challenges. The diversity of application scenarios and the complexity of application processes can be effectively addressed through modeling. This paper proposes a modeling approach for manufacturing scenario sensing and edge decision-making. Firstly, an abstract meta-model (SMM) is defined, which provides a unified description of the resources and processes in the scenario and the interaction between the scenario and the edge. Based on the meta-model, an application scenario model (ASM) can be constructed for a specific scenario to support edge data feedback and decision-making for abnormal events. In addition, the model is constructed in a scenario modeling tool and validated in a simulated manufacturing production line, that is, whether the models can provide effective support for decision-making of abnormal events. The results demonstrate that mapping normalized models into codes at the edge computing nodes can improve the accuracy and real-time performance of decision-making.\",\"PeriodicalId\":369407,\"journal\":{\"name\":\"2023 IEEE International Conference on Edge Computing and Communications (EDGE)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Conference on Edge Computing and Communications (EDGE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EDGE60047.2023.00028\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Edge Computing and Communications (EDGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDGE60047.2023.00028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Domain modeling for scenario sensing and edge decision-making
The introduction of numerous edge computing nodes allows application systems to sense and make decisions in real-time but also brings new challenges. The diversity of application scenarios and the complexity of application processes can be effectively addressed through modeling. This paper proposes a modeling approach for manufacturing scenario sensing and edge decision-making. Firstly, an abstract meta-model (SMM) is defined, which provides a unified description of the resources and processes in the scenario and the interaction between the scenario and the edge. Based on the meta-model, an application scenario model (ASM) can be constructed for a specific scenario to support edge data feedback and decision-making for abnormal events. In addition, the model is constructed in a scenario modeling tool and validated in a simulated manufacturing production line, that is, whether the models can provide effective support for decision-making of abnormal events. The results demonstrate that mapping normalized models into codes at the edge computing nodes can improve the accuracy and real-time performance of decision-making.