异构工业系统的数据集成模型:概念分析

Abdullah Aziz, O. Schelén, Ulf Bodin
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引用次数: 1

摘要

在工业自动化领域,异构系统和体系结构之间的数据集成是一个挑战。企业和工厂对于选择有利于本地需求的技术解决方案缺乏耐心,因此面临数据集成和其他系统之间不兼容的问题。需要连接异构工业系统以提供数据集成。本文旨在为工业管理者和解决方案设计者提供指导,以根据其需求实现异构工业系统之间的数据集成。为此,我们探索了两种数据集成模型的实现,可以根据工业系统的状态和需求进行选择。第一个数据集成模型基于事件驱动的体系结构(EDA),其中将消息队列遥测传输(MQTT)部署为事件代理。第二个模型基于箭头框架,该框架是通过使用面向服务的体系结构(SOA)原则设计的,其中EventHandler提供基于SOA的事件驱动通信。我们根据工业环境中必不可少的选定标准,从概念上比较和分析它们。这些模型的定性分析是基于为我们的评估提供的概念验证实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Integration Models for Heterogeneous Industrial Systems: A Conceptual Analysis
In the industrial automation domain, data integration between heterogeneous systems and architectures is a challenge. Companies and factories are impatient with the selection of technical solutions that are beneficial to local requirements, therefore facing problems of data integration and incompatibility between other systems. There is a need to bridge heterogeneous industrial systems to provide data integration. This article aims to provide guidelines to industrial managers and solution designers to achieve data integration between heterogeneous industrial systems according to their requirements. For this purpose, we have explored the implementation of two data integration models that can be selected based on the state and needs of industrial systems. The first data integration model is based on event-driven architecture (EDA), where Message Queuing Telemetry Transport (MQTT) is deployed as an event broker. The second model is based on the Arrowhead Framework, which is designed by using service-oriented architecture (SOA) principles, where EventHandler provides SOA-based event-driven communication. We conceptually compare and analyze them based on selected criteria essential in an industrial environment. The qualitative analysis of these models is based on proof-of-concept implementations made available for our evaluation.
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