Q uantitative e valuation of e mbedded s ystems
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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. Marco Zuniga (TUD). Pieter Cuijpers (TU/e). Anne Remke (UT). Marielle Stoelinga (UT).

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Q uantitative e valuation of e mbedded s ystems

Quantitative Evaluation of Embedded Systems

  • Mutual introductions

  • The context of the course: Model Based / Driven Design

  • Organisation of the course


Introducing the lecturers
Introducing the lecturers

Marco Zuniga (TUD)

Pieter Cuijpers (TU/e)

Anne Remke (UT)

MarielleStoelinga (UT)


Why a tele lecture
Why a tele-lecture ?

  • Link between education and research

  • 3TU cooperation :Specialization in research vs Broad engineering education

  • Efficiency


Why a class room
Why a class-room ?

flipped

  • More time for questions & (tele)-communication

  • Rewind button

  • Better insight in your progress

  • More convenient homework


Last years evaluation warning
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




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


The engineering design cycle
The Engineering Design Cycle

Specification

Design

Implementation

Deployment & Maintenance

THE COST OF FIXING SOFTWARE BUGS (BOEHM)


Model based design
Model Based Design

Specification

Design

Implementation

Model Checking

Deployment & Maintenance


Model driven design
Model Driven Design

Specification

Design

Implementation

State space exploration

Programming paradigms

Code Generation

Deployment & Maintenance


Next generation computing
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!


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


Contents of the course
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 systems
Case: Cyber Physical Systems

Computation

Communication network

Cyber

Physical

Control

Sensing

Acting

Physical World


Case cyber physical systems1
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


General planning of qees
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





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