Q uantitative E valuation of E mbedded S ystems

1. Quantitative Evaluation of Embedded Systems • Mutual introductions • The context of the course: Model Based / Driven Design • Organisation of the course

2. Introducing the lecturers Marco Zuniga (TUD) Pieter Cuijpers (TU/e) Anne Remke (UT) MarielleStoelinga (UT)

3. Why a tele-lecture ? • Link between education and research • 3TU cooperation :Specialization in research vs Broad engineering education • Efficiency

4. Why a class-room ? flipped • More time for questions & (tele)-communication • Rewind button • Better insight in your progress • More convenient homework

5. Last years evaluation (warning) • Bad tele-connections • Three (too) different topics • Too many notational conventions • Too abstract for hands-onembedded systems enthousiasts • Too much mandatory homework

6. Who are you?

7. Who are you?

8. bandwidth energy timing battery drain up-time overflow chance of failure Model-based Design worst-case average-case package loss latency memory cost deadline miss throughput measurements best-case time-outs robustness

9. The Engineering Design Cycle Specification Design Implementation Deployment & Maintenance THE COST OF FIXING SOFTWARE BUGS (BOEHM)

10. Model Based Design Specification Design Implementation Model Checking Deployment & Maintenance

11. Model Driven Design Specification Design Implementation State space exploration Programming paradigms Code Generation Deployment & Maintenance

12. Next Generation Computing Quality = Quantity • Deadlines • Power usage • Fault tolerance • Performance Trends: • Complex • Highly networked • Failures = fact of life Needed: • Systematic Quant. Analysis at Design-time • Multi-disc. approach • QEES!

13. State based Petri-nets Probabilistic Parameterized Timed Data Discrete Max-plus algebra Differential equations Continuous Event based Automata Dynamic Behavior convex Model Checking CTL* monotone Quantitative (Numerical) Properties Qualitative (Logical) pCTL linear LTL tCTL modal µ-calculus

14. Contents of the course • 3 Typical quantitative formalisms: Dataflow, Timed Automata, Markov Chains • 1 Quantitative analysis method for Dataflow • 3 Model-checking methods for TA and MC • 3 Tools: SDF3, UPPAAL, PRISM • 1 Case study

15. Case: Cyber Physical Systems Computation Communication network Cyber Physical Control Sensing Acting Physical World

16. Case: Cyber Physical Systems Determine an appropriate communication schedule that guarantees given latency and throughput constraints for this control network and predict the associated network load. Sensor 1 Temperature Actor 1 Valve Comp. Inner control Sensor 2 Pressure Actor 2 Motor xyz Comp. Emergency detection Sensor 3 Camera Actor 3 Motor rot. Comp. Image processing Sensor 4 Microphone Physical World

17. General planning of QEES • Dataflow - Timed Automata - Probabilistic Automata • Tele-lectures & flipped classroom • Watch videos at home… …make exercises in class • Some additional material in class • One mandatory assignment (pass/fail)(One case-study document – to be updated 3 times) • One exam

18. Program for Dataflow

19. Program for Timed Automata

20. Program for Markov Chains