A messaging library for distributed modeling

作     者：Jan Zenisek Florian Bachinger Dominik Falkner Erik Pitzer Stefan Wagner Alfredo Lopez Michael Affenzeller 

作者机构：Heuristic and Evolutionary Algorithms Laboratory University of Applied Sciences Upper Austria Softwarepark 11 Hagenberg 4232 Austria Institute for Symbolic Artificial Intelligence Johannes Kepler University Altenberger Straße 69 Linz 4040 Austria RISC Software GmbH Softwarepark 32a Hagenberg 4232 Austria Software Competence Center Hagenberg GmbH (SCCH) Softwarepark 32a Hagenberg 4232 Austria 

出 版 物：《Procedia Computer Science》 

年 卷 期：2024年第232卷

页      面：606-615页

主　　题：Software Design Message-Oriented Middleware Open Source Industrial Machine Learning Industry 4.0 

摘      要：The ongoing digital transformation of industry is most clearly reflected in the increasing collection and analysis of data from various sources. Among these are sensor equipped machinery, telemetry in logistics or audiovisually monitored production floors. In order to utilize the data, e. g., to predict machinery malfunctions, its technically smooth consolidation is crucial. Therefore, numerous data interchange formats, protocols and middleware emerged over the past years. However, until today there is no gold standard technology stack for industrial data analysis, for multiple reasons, including the applications’ heterogeneity. In this work, we present a software library which aims at decoupling messaging protocols and patterns from their implementation to overcome incompatibilities and, thus, facilitate data consolidation for software engineers. Moreover, we show how to use the library for rapidly modeling distributed cyber-physical systems using an integrated schema generation mechanism. Based on one real-world and one synthetic use case, we evaluate the library s applicability, discuss open issues and outline planned features.