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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
slide8

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!
slide13

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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