Industrial Control via Application Containers: Migrating from Bare-Metal to IAAS

Hofer, Florian; Sehr, Martin A.; Iannopollo, Antonio; Ugalde, Ines; Sangiovanni‐Vincentelli, Alberto; Russo, Barbara

doi:10.1109/cloudcom.2019.00021

Cited by 19 publications

(20 citation statements)

References 18 publications

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“…Hofer et al [18] use the real-time containers in the context of control applications. The paper presents comparison between type 1 hypervisor, Vanilla Linux, Xenomai co-kernel and Linux with real-time patch for various idle and stress scenarios.…”

Section: Methods Based On Real-time Co-kernelmentioning

confidence: 99%

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Efficient Hosting of Robust IoT Applications on Edge Computing Platform

Avasalcai

Zarrin²,

Pop³

et al. 2020

2020 IEEE 4th International Conference on Fog and Edge Computing (ICFEC)

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Container-based virtualization has gained a significant importance in a deployment of software applications in cloud-based environments. The technology fully relies on operating system features and does not require a virtualization layer (hypervisor) that introduces a performance degradation. Container-based virtualization allows to co-locate multiple isolated containers on a single computation node as well as to decompose an application into multiple containers distributed among several hosts (e.g., in fog computing layer). Such a technology seems very promising in other domains as well, e.g., in industrial automation, automotive, and aviation industry where mixed criticality containerized applications from various vendors can be co-located on shared resources.However, such industrial domains often require real-time behavior (i.e, a capability to meet predefined deadlines). These capabilities are not fully supported by the container-based virtualization yet. In this work, we provide a systematic literature survey study that summarizes the effort of the research community on bringing real-time properties in container-based virtualization. We categorize existing work into main research areas and identify possible immature points of the technology.

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Section: Methods Based On Real-time Co-kernelmentioning

confidence: 99%

“…The need for an orchestration tool that can schedule real-time containers based on pre-configured capabilities [18]. Middleware that is aware of both communication needs as well as run-time and performance isolation needs [22].…”

Section: Challenges Of Real-time Container-based Virtualizationmentioning

confidence: 99%

Efficient Hosting of Robust IoT Applications on Edge Computing Platform

Avasalcai

Zarrin²,

Pop³

et al. 2020

2020 IEEE 4th International Conference on Fog and Edge Computing (ICFEC)

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“…This makes them lighter and more portable, with significantly less overhead. [14], [15] and [16] have focused their work on demonstrating their feasibility from a time constraints point of view and implementing controllers directly as programmable logic controllers (PLC) and also supporting time constraints and general features for real-time applications. Other works [17], [18], [19] and [20] presents great utility on the cloud computing side, showing its applications deployed in a microservice architecture.…”

Section: B Containers Based Technologymentioning

confidence: 99%

Component-Based Microservices for Flexible and Scalable Automation of Industrial Bioprocesses

et al. 2021

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Industry 4.0 involves the digital transformation of the industry with the integration and digitization of all industrial processes that make up the value chain, which is characterized by adaptability, flexibility, and efficiency to meet the needs of customers in today's market. Therefore, the adaptations of the new bioprocess industry require a lot of flexibility to react quickly and constantly to market changes and to be able to offer more specialized, customized products with high operational efficiency. This paper presents a flexible, scalable, and robust framework based on software components, container technology, microservice concepts, and the publish/subscribe paradigm. This framework allows new components to be added or removed online, without the need for system reconfiguration, while maintaining temporal and functional constraints in industrial automation systems. The main objective of the framework proposed is the use of components based on microservices, allowing easy implementation, scalability, and fast maintenance, without losing or degrading the robustness from previous developments. Finally, the effectiveness of the proposed framework was verified in two case studies (1) a soursop soda making process is presented, with a fuzzy controller implemented to keep the pasteurizer output flow constant (UHT) and (2) an automatic storage tank selection and filling process with actuated valves to direct the fluid to the corresponding tank at the time to start the process. The results showed that the platform provided a high-fidelity design, analysis, and testing environment for the flow of cyber information and its effect on the physical operation in a beverage processing plant with high demand for flexibility, scalability, and robustness of its processes, as they were experimentally verified in a real production process.INDEX TERMS Industry 4.0, distributed industrial automation systems, interoperability, middleware, industrial cyber-physical systems.

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“…With these technologies, we configured a real-time container engine and built and ran a containerized real-time application. Our experiments showed that the containers could be grouped and orchestrated using the Linux kernel's CGroups feature to optimize resource 37 The selected configuration is used for the new performance and optimization tests in Section 6.3.…”

Section: Selection Of the Off-the-shelf Os And Containerization Toolsmentioning

confidence: 99%

“…Both kernel versions with patches described in Section 6.2 can be built and restored for all three architectures using our automated script, available online. 43 Further details, the script executing all the tests, the installation scripts, the experiment data, and technical details and results are available in Hofer et al 37 This extra effort must be taken into account when evaluating a migration strategy. The introduced distance between control cloud and onsite devices may also require more time-critical communication protocols respecting standards such as the TSN family, which may add some overhead.…”

Section: Scripts and Tools Developed For The Testsmentioning

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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Industrial Control via Application Containers: Migrating from Bare-Metal to IAAS

Cited by 19 publications

References 18 publications

Efficient Hosting of Robust IoT Applications on Edge Computing Platform

Efficient Hosting of Robust IoT Applications on Edge Computing Platform

Component-Based Microservices for Flexible and Scalable Automation of Industrial Bioprocesses

Industrial control via application containers: Maintaining determinism in IAAS

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