Kubernetes Orchestration of High Availability Distributed Control Systems
2022 (English)In: Proc IEEE Int Conf Ind Technol, Institute of Electrical and Electronics Engineers Inc. , 2022Conference paper, Published paper (Refereed)
Abstract [en]
Distributed control systems transform with the Industry 4.0 paradigm shift. A mesh-like, network-centric topology replaces the traditional controller-centered architecture, enforcing the interest of cloud-, fog-, and edge-computing, where lightweight container-based virtualization is a cornerstone. Kubernetes is a well-known container management system for container orchestration in cloud computing. It is gaining traction in edge- and fog-computing due to its elasticity and failure recovery properties. Orchestrator failure recovery can complement the manual replacement of a failed controller and, combined with controller redundancy, provide a pseudo-one-out-of-many redundancy. This paper investigates the failure recovery performance obtained from an out-of-the-box Kubernetes installation in a distributed control system scenario. We describe a Kubernetes based virtualized controller architecture and the software needed to set up a bare-metal cluster for control systems. Further, we deploy single and redundant configured containerized controllers based on an OPC UA compatible industry middleware software on the bare-metal cluster. The controllers expose variables with OPC UA PubSub. A script-based daemon introduces node failures, and a verification controller measures the downtime when using Kubernetes with an industry redundancy solution.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2022.
Keywords [en]
Cluster computing, Containers, Distributed parameter control systems, Fault tolerance, Fog computing, Middleware, Network architecture, Redundancy, Bare metals, Container management, Edge computing, Failure recovery, High availability, Management systems, Metal cluster, Network-centric, Paradigm shifts, Virtualizations, Controllers
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-62523DOI: 10.1109/ICIT48603.2022.10002757Scopus ID: 2-s2.0-85131518888ISBN: 9781728119489 (print)OAI: oai:DiVA.org:mdh-62523DiVA, id: diva2:1761053
Conference
Proceedings of the IEEE International Conference on Industrial Technology
2023-05-312023-05-312024-01-18Bibliographically approved