Intelligent devices, interconnectivity, and information exchange are characteristics often associated with Industry 4.0. A peer-to-peer-oriented architecture with the network as the system center succeeds the traditional controller-centric topology used in today's distributed control systems, improving information exchange in future designs. The network-centric architecture allows IT-solution such as cloud, fog, and edge computing to enter the automation industry. IT-solution that rely on virtualization techniques such as virtual machines and containers. Virtualization technology, combined with virtual instance management, provide the famous elasticity that cloud computing offer. Container management systems like Kubernetes can scale the number of containers to match the service demand and redeploy containers affected by failures. Distributed control systems constitute automation infrastructure core in many critical applications and domains. The criticality puts high dependability requirements upon the systems, i.e., dependability is essential. High-quality software and redundancy solutions are examples of traditional ways to increase dependability. Dependability is the common denominator for the challenges addressed in this thesis. Challenges that range from concurrency defect localization with static code analysis to utilization of failure recovery mechanisms provided by container management systems in a control system context. We evaluate the feasibility of locating concurrency defects in embedded industrial software with static code analysis. Furthermore, we propose a deployment agnostic failure detection and role selection mechanism for controller redundancy in a network-centric context. Finally, we use the container management system Kubernetes to orchestrate a cluster of virtualized controllers. We evaluate the failure recovery properties of the container management system in combination with redundant virtualized controllers - redundant controllers using the proposed failure detection and role selection solution.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mdh-60071 |
Date | January 2022 |
Creators | Johansson, Bjarne |
Publisher | Mälardalens universitet, Inbyggda system, ABB AB, Västerås |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Licentiate thesis, comprehensive summary, info:eu-repo/semantics/masterThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
Relation | Mälardalen University Press Licentiate Theses, 1651-9256 ; 330 |
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