Architecture, technologies and challenges for cyber-physical systems in industry 4.0

Hofer, Florian

doi:10.1145/3239235.3239242

Cited by 30 publications

(28 citation statements)

References 49 publications

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“…This restriction particularly impacts deterministic (hard) real-time systems that must know in advance that every task i will complete within its deadline d i . 22,23 In this work, we aim to assess alternative architectural configurations for a control system migrated to a virtualized and containerized environment while maintaining the original level of the system's determinism 2 running in a bare-metal environment.…”

Section: Research Questions and Approach Previewmentioning

confidence: 99%

Industrial control via application containers: Maintaining determinism in IAAS

Hofer

Sehr

Sangiovanni-Vincentelli

et al. 2021

Systems Engineering

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Industry 4.0 is changing data collection, storage, and analysis in industrial processes fundamentally, enabling novel applications such as flexible manufacturing of highly customized products. However, real-time control of these processes has not yet realized its full potential in using the collected data to drive further development. Indeed, typical industrial control systems are tailored to the plant they need to control, reusing, and adapting to challenge. In the past, the need to solve plant-specific problems overshadowed the benefits of physically isolating a control system from its plant. We believe that modern virtualization techniques, specifically application containers, present a unique opportunity to decouple control from plants. This separation permits us to fully realize the potential for highly distributed and transferable industrial processes even with real-time constraints arising from time-critical subprocesses. This paper explores the challenges and opportunities of shifting industrial control software from dedicated hardware to bare-metal servers or (edge) cloud computing platforms using off-the-shelf technology, that is, technologies commercially available. We present a migration architecture and show, using a specifically developed orchestration tool, that containerized applications can run on shared resources without compromising scheduled execution within given time constraints. Through latency and computational performance experiments, we explore three system setups' limits and summarize lessons learned. K E Y W O R D S container orchestration, determinism, IAAS, industrial control systems, real-time 1 INTRODUCTION Emerging technologies such as the Internet of Things and Cloud Computing offer the chance to innovate structure and control of industrial processes. These new technologies allow the creation of flexible production systems, for which control is performed through distributed sensing, big-data analysis, and cloud storage. Such systems may also take advantage of new computing paradigms like the Edge Networking paradigm or the Fog Computing, which brings data stor-This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Research Questions and Approach Previewmentioning

confidence: 99%

Industrial control via application containers: Maintaining determinism in IAAS

Hofer

Sehr

Sangiovanni-Vincentelli

et al. 2021

Systems Engineering

Self Cite

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“…Other categories of terms commonly mentioned are system components (eg. web services, control system), deployment details (virtual machine, private cloud) and industry standards like OPC UA 4 and SCADA systems [15].…”

Section: Rq1mentioning

confidence: 99%

“…Figure 8 shows the distribution of the mentioned application areas within the publications over the years. The most fre- 4 https://opcfoundation.org/about/opc-technologies/opc-ua/ quently mentioned application areas are smart grid and mobile cloud followed by smart city and cloud manufacturing. Both smart grid and mobile cloud reached a peak in the number of publications in the year 2018.…”

Section: Rq1mentioning

confidence: 99%

“…An overview of how CCPS architectures are described in the literature can provide a crucial starting point for CCPS architecture description and system development. Towards this direction, a survey focusing on mobile robots, wireless sensor networks and vehicular networks as different kinds of CCPS has been provided in [1] and a systematic mapping study discussing cyber-physical systems in Industry 4.0 was presented in [4]. However, both of these works focus on specific application areas and do not provide a systematic overview of the research on CCPS architectures.…”

Section: Introductionmentioning

confidence: 99%

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Architectures of Cloud-enabled Cyber Physical Systems — a Systematic Mapping Study

Reuter

Andrikopoulos

2020

2020 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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Cloud enabled Cyber Physical Systems (CCPS) combine embedded systems with highly scalable cloud services. Such systems provide opportunities to offload computing or data analytics tasks which require more resources than an embedded device can offer. The development of a CCPS involves multiple stakeholders as well as engineers and developers from different disciplines, which makes the description and communication of the system architecture a challenging task. Additionally, the architecture design of CCPS has the inherent challenge to determine which functionality should be placed on the device, in the cloud, or on a possible fog/edge device within or close to the system. This systematic mapping study evaluates how CCPS architectures are discussed in the current literature and which topics are associated with cloud computing in CCPS architectures. The results show a significant increase in CCPS publications over the last years, a focus on a specific architectural viewpoint and application areas, and a potential misalignment with the common understanding of cloud computing as a paradigm.

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“…Consequently, Edge Computing including cross-platform operation, third party software and mixed criticality applications are increasingly more important. The computation requirements given the migration of functionality towards the "edge" imply new system architectures [1], [2].…”

Section: Introductionmentioning

confidence: 99%