Today’s systems for automation and control are often complex compositions of various hardware and software pieces. Furthermore, this complexity rapidly increases as emerging and future systems become more and more smart, like the industrial Internet of things or autonomous driving systems. A system architecture is a collection of rules and guidelines that aim to manage this complexity. This lecture will address both practical and theoretical aspects of system architectures. Students will become aware of the system complexity problem, learn industrial solutions to manage this complexity, and will understand background theories.

• System Architecture: Definition,  Lecture Scope, Problem Formulation
• System properties: Dependability, Security, Real-Time Response, Maintainability, Cost, etc.
• Practical Examples:
• Overview:  from IT (Office, Datacenter, etc.) to OT (Industrial Automation, Avionics, etc.)
• From Cloud to Fog Computing
• Next Generation Automotive System Architectures
• Technologies on the Rise
• Middleware, e.g., ROS, TTIntegration, CodeSys
• Hypervisors, e.g., PikeOS, LyncSecure, QNX
• Networks, e.g., TSN, OPC UA, DDS
• Theory
• Models of Computation (MoC)
• Time-Triggered Architecture (TTA)
• Physically-Asynchronous Logically-Synchronous Architecture (PALS)
• Globally-Asynchronous Locally-Synchronous (GALS)
• Loosely Time-Triggered Architecture (LTTA)
• A Framework for High-Assurance Quasi-Synchronous Systems (SRI)
• Interface Theory
• Multiple Independent Levels of Safety and Security (MILS) and Distributed MILS

Vorlesungsfolien und zusätzliche Literatur werden zur Verfügung gestellt

Mündliche Prüfung