Engin Yoeyen

• This master thesis presents a collection of architectural design patterns for safety-critical systems deployed on public cloud infrastructure. The research aims to enhance system reliability, mitigate risks, and improve overall performance in safety-critical applications. The study follows a systematic approach, considering multiple safety-critical use cases and prioritizing factors such as timing constraints and system resilience. The railway signaling system, particularly the moving block computation, is selected as the most suitable use case due to its ability to tolerate response delays and re-request computations. The thesis addresses four research questions concerning the deployment of safety-critical systems to the public cloud, existing fault-tolerance methods in the cloud, identification of relevant design patterns, and the applicability of design patterns in various safety-critical systems. The study identifies and review's fault tolerance methods and cloud failure modes, which serve as a basis for identifying design patterns. The Structured What-If Technique (SWIFT) is utilized to analyze prospective hazards and recommend actions, which are then mapped onto design patterns for wide applicability across different projects. Each design pattern presents a problem statement, guidelines for implementation, and associated benefits and drawbacks. The contribution of this thesis lies in the development of a valuable resource for architects and engineers working on safety-critical systems in the cloud. The design patterns offer practical solutions and a framework for the design and implementation of robust and secure systems. Detailed documentation, including context, benefits, drawbacks, and practical examples, facilitates understanding and adoption. In conclusion, this thesis contributes to the advancement of safety and reliability in cloud-based safety-critical systems by providing architectural design patterns. Future research should focus on integrating security aspects, gathering diverse use cases, and validating the patterns in practical settings. Continued exploration and refinement of the design patterns will lead to more robust solutions for meeting the needs and challenges of safety-critical applications in various contexts.