We explore the challenges and opportunities of shifting industrial control software from dedicated hardware to bare-met al servers or cloud computing platforms using off the shelf technologies. In particular, we demonstrate that executing time-critical applications on cloud platforms is viable based on a series of dedicated latency tests targeting relevant real-time configurations.
Goldschmidt and Hauk-Stattelmann in @cite_9 perform benchmark tests on modularized industrial Programmable Logic Controller (PLC) applications. This analysis analyzes the impact of container-based virtualization on real-time constraints. As there is no solution for legacy code migration of PLCs, the migration to application containers could extend a system's lifetime beyond the physical device's limits. Even though tests showed worst-case latencies of the order of @math on Intel-based hosts, the authors argue that the container engines may be stripped down and optimized for real-time execution. In a follow-up work, @cite_28 , a possible multi-purpose architecture was described and tested in a real-world use case. The results show worst case latencies in the range of @math for a Raspberry PI single-board computer, making the solution viable for cycle times in the range of @math to @math . The authors state that topics such as memory overhead, containers' restricted access and problems due to technology immaturity are still to be investigated.
@cite_28 @cite_9
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Abstract Cyber-physical systems and the Internet-of-Things are getting more and more traction in different application areas. Boosted by initiatives such as Industrie 4.0 in Germany or the Industrial Internet Consortium in the US, they are enablers for innovation in industrial automation. To provide the advanced flexibility in production envisioned for future automation systems, Programmable Logic Controllers (PLCs), as one of their main building blocks, also need to become more flexible. However, the conservative nature of this domain prohibits changes in the controller architecture impacting the installed base. Currently there exist various approaches that evolve control architectures to the next level, but none of them address flexible function deployment at the same time with legacy support. In this paper, we present an architecture for a multi-purpose controller that is inspired by the virtualization trend in cloud systems which moves from heavyweight virtual machines to lightweight containers solutions such as LXC or Docker. Our solution includes the support for multiple PLC execution engines and adds support for the emulation of legacy engines as well. We evaluate this architecture by executing performance measurements that analyze the impact of container technologies to the real-time aspects of PLC engines. Cyber-physical systems and the Internet-of-Things are getting more and more traction in different application areas. Boosted by initiatives such as Industrie 4.0 in Germany or the Industrial Internet Consortium in the US, they are enablers for innovation in industrial automation. To provide the advanced flexibility in production envisioned for future automation systems, Programmable Logic Controllers (PLCs), as one of their main building blocks, also need to become more flexible. However, the conservative nature of this domain prohibits changes in the controller architecture impacting the installed base. Currently there exist various approaches that evolve control architectures to the next level, but none of them address flexible function deployment at the same time with legacy support. In this paper, we present a an architecture for a multi-purpose controller that is inspired by the virtualization trend in cloud systems which moves from heavyweight virtual machines to lightweight containers solutions such as LXC or Docker. Our solution includes the support for multiple PLC execution engines and adds support for the emulation of legacy engines as well. We evaluate this architecture by executing performance measurements that analyze the impact of container technologies to the real-time aspects of PLC engines.