Ju Li, Jiawen Xiong, Xia Mao, Jianqi Shi, Xin Ye, Yanhong Huang
{"title":"Decomposition and Collaboration of Industrial Control System with Resource Constraints","authors":"Ju Li, Jiawen Xiong, Xia Mao, Jianqi Shi, Xin Ye, Yanhong Huang","doi":"10.1109/ICECCS.2017.25","DOIUrl":null,"url":null,"abstract":"With the development of \"Industry 4.0\", the scale and complexity of industrial control system grow rapidly. Hence, the analysis and verification of such systems face really big challenges. Industry requires a reliable approach for decomposing the existing complex system model to multiple fine-grained and interactive models. In this paper, we propose a general event-triggered language named IMCL for modeling industrial control systems. IMCL can describe the physical resources and system in one unified model. Following the given physical resource constraints, we present the reliable and efficient decomposition and collaboration algorithms based on IMCL models to meet the industrial requirements. In particular, we have implemented these algorithms in a tool and get same encouraging results.","PeriodicalId":114056,"journal":{"name":"2017 22nd International Conference on Engineering of Complex Computer Systems (ICECCS)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 22nd International Conference on Engineering of Complex Computer Systems (ICECCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECCS.2017.25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the development of "Industry 4.0", the scale and complexity of industrial control system grow rapidly. Hence, the analysis and verification of such systems face really big challenges. Industry requires a reliable approach for decomposing the existing complex system model to multiple fine-grained and interactive models. In this paper, we propose a general event-triggered language named IMCL for modeling industrial control systems. IMCL can describe the physical resources and system in one unified model. Following the given physical resource constraints, we present the reliable and efficient decomposition and collaboration algorithms based on IMCL models to meet the industrial requirements. In particular, we have implemented these algorithms in a tool and get same encouraging results.