TY - JOUR
T1 - A messaging library for distributed modeling
AU - Zenisek, Jan
AU - Bachinger, Florian
AU - Falkner, Dominik
AU - Pitzer, Erik
AU - Wagner, Stefan
AU - Lopez, Alfredo
AU - Affenzeller, Michael
N1 - Publisher Copyright:
© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Industrial Machine Learning
KW - Industry 4.0
KW - Message-Oriented Middleware
KW - Open Source
KW - Software Design
UR - http://www.scopus.com/inward/record.url?scp=85189809669&partnerID=8YFLogxK
U2 - 10.1016/j.procs.2024.01.060
DO - 10.1016/j.procs.2024.01.060
M3 - Conference article
AN - SCOPUS:85189809669
SN - 1877-0509
VL - 232
SP - 606
EP - 615
JO - Procedia Computer Science
JF - Procedia Computer Science
T2 - 5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023
Y2 - 22 November 2023 through 24 November 2023
ER -