Q uantitative E valuation of E mbedded S ystems Mutual introductions The context of the course: Model Based / Driven Design Organisation of the course

Introducing the lecturers Anne Remke (UT) Pieter Cuijpers (TU/e) Marielle Stoelinga (UT) Marco Zuniga (TUD)

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

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

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

Who are you? BSc Electrical EngBSc Computer ScienceOther TU/e TUD UT

Who are you? Logic & Set- theory Petri- nets Finite Autom. Linear algebra Prob.th.Model checking TU/e TUD UT

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

Specification Design Implementation Deployment & Maintenance Model Based Design Model Checking

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

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

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

Case: Cyber Physical SystemsComputation Physical World Communication network

Case: Cyber Physical Systems Comp. Inner control Physical World Comp. Emergency detection Comp. Image processing Determine an appropriate communication schedule that guarantees given latency and throughput constraints for this control network and predict the associated network load.

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

Program for Dataflow DateWeblecture - at homeAdditional – in classExercises – in class ’131 – intro dataflow (This one we’ll watch in class) Intro to QEES Counters and daters Simulate a given graph and set up matrix equations for it ’132 – throughput 3 – periodic schedule (watch these at home, in the train, wherever, but not in class!) Eigenvalues and linear programs Determine the MCM and periodic schedule for a graph ’134 – latency 1 5 – latency 2 Monotonicity Determine the latency of a graph ’136 – buffering 7 – latency 3 TDMA + intro assignment, multi-rate, intro to SDF3 Determine minimum buffersizes of a graph. Deadline: 9-DEC-2013 : As a first step in the case study, you will model a small cyber-physical control network in SDF3, in which TDMA communication using wirelessHART is used. You will analyse worst-case latency and throughput that is achieved, and add buffers to determine the network load.

Program for Timed Automata DateWeblecture - at homeAdditional – in classExercises – in class ’13Intro Timed Automata Modeling and analysis of a small resource scheduling problem ’13ES-Day in Delft : GUEST LECTURE Arjen Mooij : Model Based Design 2-12-’13UPPAAL under the hood Practice semantics and composition 6-12-’13UPPAAL under the hood Practice R.A ’13Paper – “Scheduling of data paths in printers” Discussion paper Intro part 2 of the assignment Wrap up of exercises Q&A Deadline: 6-JAN-2013 : As a second step in the case study, you will use UPPAAL to make an optimal TDMA schedule for the cyber-physical system and see how latency and throughput are improved. These results are then fed back into the dataflow model.

Program for Markov Chains DateWeblecture - at homeAdditional – in classExercises – in class ’13CTL (This one we’ll watch in class) Markov Chains CTL ’13CTL model checkingDiscr. Timed Markov Chains CTL model checking ’13PCTL model checking DTMC & PCTL model checking 6-1-’14Paper: “Wireless HART”Perf. eval. of Wireless HART Cont. Timed Markov Chains 10-1-’14CSL model checking 13-1-’14Q&A 17-1-’14Q&A Deadline: 17-JAN-2013 : As a final step in the case study, you will analyze the effect of message loss on the optimal TDMA schedule you found previously. Furthermore, you will discuss in a concluding chapter the different roles of the three formalisms studied in this course in the engineering design-cycle.