A key feature of cloud computing is elasticity, which enables resources to be allocated and de-allocated according to dynamic application demands. The evolution of Industrial Control Systems (ICS) is moving towards a distributed converged infrastructure that incorporates computing and communication resources as well as software, replacing dedicated hardware running control applications. While modern ICS and cloud environments share similarities, the corresponding applications differ significantly in their execution models and timing requirements. To enhance the flexibility of ICS, control applications must adapt to changing requirements throughout operation, resulting in varying workloads. The potential for dynamic scaling in ICS is considerable, but is not yet being fully exploited. The objective of this paper is to examine the extent to which state-of-the-art cloud autoscaling concepts are applicable to the scaling of real-time workloads and to propose enhancements to these concepts in order to enable the implementation of dynamic auto scaling of real-time workloads. In conclusion, the fundamental concept of cloud autoscaling can be applied, but must be extended, in particular to ensure deterministic resource provisioning and to improve task isolation in order to guarantee predictable task timing behaviour.

Distributed real-time applications perform deterministic tasks across multiple connected compute platforms, referred to as endpoints. Deterministic behavior of the communication and the compute are prerequisites, but coordinating and managing both in a holistic way is a significant challenge. Converged real-time networks based on Time-Sensitive Networking (TSN) are considered the key enabler across industries for the required connectivity. To date, the potential of TSN cannot be exploited due to many sub-standards still being under development, gaps in the management and configuration functions, lack of best practices and unresolved integration with higher application layers and domain specific engineering. Previous work, focusing on a modular open source framework for the engineering and management of distributed real-time applications, identified a unified approach for TSN-based endpoints as a key gap. This paper presents a novel endpoint architecture to operate, engineer and manage distributed real-time applications by seamlessly integrating real-time networking and compute. The architecture provides interfaces to a central engineering, allows to integrate centralized as well as distributed network management and offers a unified data management. An abstraction layer for applications allows the efficient use and complements existing open source solutions.

TSN, or Time Sensitive Networking, is becoming an essential technology for integrated networks, enabling deterministic and best effort traffic to coexist on the same infrastructure. In order to properly configure, run and secure such TSN, monitoring functionality is a must. The TSN standard already has some preparations to provide such functionality and there are different methods to choose from. We implemented different methods to measure the time synchronisation accuracy between devices as a C library and compared the measurement results. Furthermore, the library has been integrated into the ControlTSN engineering framework.

The digitalization of production is a strategic goal in the automation industry, though visions and industrial reality remain far apart. A key issue is that today's segmented communication architecture based on fieldbus networks does not fulfill the future requirements. Converged networks connecting IT and OT systems while maintaining deterministic guarantees for real-time communication are required instead. Time Sensitive Networking (TSN) in the context of IEEE 802.1 Ethernet is a key enabling technology for converged networks. The transition from current communication architectures towards converged networks will not be a disruptive change, but rather an evolutionary process involving many steps. In this paper, an analysis of different dimensions of this transition process and their evolutionary steps is presented. Potential migration paths from current to future production architectures and resulting intermediate brownfield scenarios are identified and analyzed with a focus on their communication architectures.

We treat problems of fair division, their various interconnections, and their relations to Sperner's lemma and the Knaster--Kuratowski--Mazurkiewicz (KKM) theorem as well as their variants. We prove extensions of Alon's necklace splitting result in certain regimes and relate it to hyperplane mass partitions. We show the existence of fair cake division and rental harmony in the sense of Su even in the absence of full information. Furthermore, we extend Sperner's lemma and the KKM theorem to (colorful) quantitative versions for polytopes and pseudomanifolds. For simplicial polytopes our results turn out to be improvements over the earlier work of De Loera, Peterson, and Su on a polytopal version of Sperner's lemma. Moreover, our results extend the work of Musin on quantitative Sperner-type results for piecewise linear manifolds.