计算机集成制造系统 ›› 2021, Vol. 27 ›› Issue (5): 1249-1255.DOI: 10.13196/j.cims.2021.05.001

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未来工业互联网松耦合结构理论、分析、评估及实现平台

赵骥1,2,齐晓锐1,2,吴教丰1,2,吴澄1   

  1. 1.清华大学国家CIMS工程技术研究中心
    2.浙江清华长三角研究院
  • 出版日期:2021-05-31 发布日期:2021-05-31
  • 基金资助:
    国家重点研发计划资助项目(2020YFB171220);浙江省重点研发计划资助项目(2021C03191)。

Future industrial Internet:Theory,analysis,evaluation of loosely coupled architecture and implementation platform

  • Online:2021-05-31 Published:2021-05-31
  • Supported by:
    Project supported by the National Key Research & Development Program,China(No.2020YFB171220),and the Key Research & Development Program of Zhejiang Province,China(No.2021C03191).

摘要: 为了解决人机物全要素安全可靠互联的系统复杂性难题,提出一种工业互联网松耦合系统结构,采用发布/订阅模式,通过多种模式的服务质量(QoS),实现全连接环境下的多维数据实时接入与处理。基于工业要素强度和信息熵中心性,构建了一种强度—信息熵中心性(SEC)评估算法,即复合中心性算法,计算系统的脆弱性与关键点。实例分析证明,SEC评估算法能够准确度量工业互联系统关键点,并在工业互联数据链平台CIMS_LINK实现该算法,通过计算系统成员SEC值并排序,监控关键成员状态,来保障松耦合联接下的工业互联系统稳定运行。

关键词: 未来工业互联网, 松耦合, 复合中心性, 强度&mdash, 信息熵中心性, 信息熵

Abstract: Industrial Internet enables the interconnection of everything including human,environment and machines.To solve the complex problem of safety and reliability of industrial interconnected system,a loosely coupled architecture was proposed.Adopting publish/subscribe model and quality of service of multiple modes,connecting and processing of the multi-dimensional data in real time was achieved.Based on the strength of industrial elements and the centrality of information entropy,a Strength-Entropy Centrality (SEC) evaluation algorithm named compound centrality algorithm was constructed to calculate the vulnerability and key points of the loosely coupled system.The experiment results showed that the proposed SEC evaluation algorithm could accurately measure the key points of industrial interconnected system,and the algorithm was employed to CIMS_LINK.System members were calculated and ranked according to the algorithm,and the state monitoring of key members was realized to ensure the stable operation of industrial interconnected system.

Key words: future industrial Internet, loose coupling, compound centrality, strength-entropy centrality, information entropy

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