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Timed Automata. Timed Automata Intelligent Light Control. press?. Off. Light. Bright. press?. Press?. Press?. WANT: if press is issued twice quickly then the light will get brighter ; otherwise the light is turned off. Timed Automata Intelligent Light Control. press?. X<=3.

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timed automata intelligent light control
Timed AutomataIntelligent Light Control

press?

Off

Light

Bright

press?

Press?

Press?

WANT: if press is issued twice quickly

then the light will get brighter; otherwise the light is

turned off.

timed automata intelligent light control1
Timed AutomataIntelligent Light Control

press?

X<=3

Off

Light

Bright

X:=0

press?

Press?

Press?

X>3

Solution: Add real-valued clock x

timed automata1
Timed Automata

(Alur & Dill 1990)

Clocks:x, y

Guard

Boolean combination of comp with

integer bounds

n

Reset

Action perfumed on clocks

Action

used

for synchronization

x<=5 & y>3

State

(location , x=v , y=u ) where v,u are in R

a

Transitions

x := 0

a

(n , x=2.4 , y=3.1415 )

(m , x=0 , y=3.1415 )

m

e(1.1)

(n , x=2.4 , y=3.1415 )

(n , x=3.5 , y=4.2415 )

timed safety automata timed automata invariants
Timed Safety Automata = Timed Automata + Invariants

(Henzinger et al, 1992)

n

Clocks:x, y

x<=5

Transitions

x<=5 & y>3

e(3.2)

Location

Invariants

(n , x=2.4 , y=3.1415 )

a

e(1.1)

(n , x=2.4 , y=3.1415 )

(n , x=3.5 , y=4.2415 )

x := 0

m

y<=10

g4

g1

Invariants ensure progress!!

g3

g2

timed automata example
Timed Automata: Example

guard

location

reset

timed automata example1
Timed Automata: Example

guard

location

reset

light switch
Light Switch

push

push

click

light switch1
Switch may be turned on whenever at least 2 time units has elapsed since last “turn off”Light Switch

push

push

click

light switch2
Switch may be turned on whenever at least 2 time units has elapsed since last “turn off”

Light automatically switches off after 9 time units.

Light Switch

push

push

click

semantics
Semantics
  • clock valuations:
  • state:
  • Semantics of timed automata is a labeledtransition systemwhere
  • action transition
  • delay Transition

g a r

l

l’

semantics example
Semantics: Example

push

push

click

networks of timed automata integer variables arrays
Networks of Timed Automata + Integer Variables + arrays ….

m1

l1

x>=2

i==3

y<=4

………….

Two-way synchronization

on complementary actions.

Closed Systems!

a!

a?

x := 0

i:=i+4

l2

m2

Example transitions

(l1, m1,………, x=2, y=3.5, i=3,…..) (l2,m2,……..,x=0, y=3.5, i=7,…..)

(l1,m1,………,x=2.2, y=3.7, I=3,…..)

tau

0.2

IfaURGENT CHANNEL

timed automata2
Timed Systems

up

lower

y <= 1

y := 0

y >= 1

raise

approach

y <= 2

y := 0

z <= 3

down

z := 0

lower

raise

exit

z <= 1

z := 0

Timed Automata

approach

far

near

x >= 1

x <= 5

x := 0

exit

enter

x := 0

x > 2

in

Train

Gate

Controller

timed automata3
Timed Systems

up

lower

y <= 1

y := 0

y >= 1

raise

approach

y <= 2

y := 0

z <= 3

down

z := 0

lower

raise

exit

z <= 1

z := 0

Timed Automata

approach

far

near

x >= 1

x <= 5

x := 0

exit

enter

x := 0

x > 2

in

Train

Gate

Controller

time

timed automata4
Timed Systems

up

lower

y <= 1

y := 0

y >= 1

raise

approach

y <= 2

y := 0

z <= 3

down

z := 0

lower

raise

exit

z <= 1

z := 0

z <= 3

Timed Automata

approach

far

near

x >= 1

x <= 5

x := 0

exit

enter

x := 0

x > 2

in

Train

Gate

Controller

approach

time

timed automata5
Timed Systems

up

lower

y <= 1

y := 0

y >= 1

raise

approach

y <= 2

y := 0

z <= 3

down

z := 0

lower

raise

exit

z <= 1

z := 0

y <= 1

Timed Automata

approach

far

near

x >= 1

x <= 5

x := 0

exit

enter

x := 0

x > 2

in

Train

Gate

Controller

approach

lower

time

z <= 3

timed automata6
Timed Systems

up

lower

y <= 1

y := 0

y >= 1

raise

approach

y <= 2

y := 0

z <= 3

down

z := 0

lower

raise

exit

z <= 1

z := 0

x = 2.1

y = 0.9

z = 2.1

Timed Automata

approach

far

near

x >= 1

x <= 5

x := 0

exit

enter

x := 0

x > 2

in

Train

Gate

Controller

approach

lower

enter

time

x > 2 x <= 5

tctl ctl time
TCTL = CTL + Time

constraints over formula clocks and automata clocks

“freeze operator” introduces new formula clock z

E[ f U f ], A[ f U f ] - like in CTL

No EX f

derived operators
Derived Operators

=

Along any path f holds continuously until within 7 time units

y becomes valid.

=

The property f may becomes valid within 5 time units.

light switch cont
Light Switch (cont)

push

push

click

timeliness properties
Timeliness Properties

receive(m) always occurs within 5 time units after send(m)

receive(m) may occur exactly 11 time units after send(m)

putbox occurs periodically (exactly) every 25 time units

(note: other putbox’s may occur in between)

fischer s protocol a simple mutex algorithm
Fischer’s ProtocolA simple MUTEX Algorithm

2

  • ´

V

Criticial Section

Init

V=1

V:=1

V=1

A1

CS1

B1

V:=2

V=2

CS2

B2

A2

fischer s protocol a simple mutex algorithm1
Fischer’s ProtocolA simple MUTEX Algorithm

2

  • ´

V

Criticial Section

X<1

X:=0

X>1

Init

V=1

V:=1

V=1

A1

CS1

B1

Y>1

Y<1

Y:=0

V:=2

V=2

CS2

B2

A2

paths
Paths

push

Example:

push

click

elapsed time in path
Elapsed time in path

Example:

s=

D(s,1)=3.5, D(s,6)=3.5+9=12.5

tctl semantics
TCTL Semantics

s - (location, clock valuation)

w - formula clock valuation

PM(s) - set of paths from s

Pos(s) - positions in s

D(s,i) - elapsed time

¥

(i,d) <<(i’,d’) iff (i

regions finite partitioning of state space1
RegionsFinite partitioning of state space

”Definition”

y

2

1

1

2

3

x

max determined

by timed automata

(and formula)

regions finite partitioning of state space2
RegionsFinite partitioning of state space

Alternative

to JPK

Definition

y

2

1

1

2

3

x

max determined

by timed automata

(and formula)

regions finite partitioning of state space3
RegionsFinite partitioning of state space

Definition

y

2

1

1

2

3

x

An equivalence class (i.e. a region)

in fact there is only a finite number of regions!!

regions finite partitioning of state space4
RegionsFinite partitioning of state space

Definition

y

2

1

r

Successor regions, Succ(r)

1

2

3

x

An equivalence class (i.e. a region)

regions finite partitioning of state space5
RegionsFinite partitioning of state space

Definition

y

2

1

THEOREM

r

{x}r

{y}r

1

2

3

x

Reset

regions

An equivalence class (i.e. a region) r

fischers again
X<1

X:=0

X>1

V:=1

V=1

A1

CS1

B1

Y>1

Y<1

Y:=0

V:=2

V=2

CS2

B2

A2

Fischers again

Untimed case

Timed case

Partial

Region Graph

A1,A2,v=1

A1,A2,v=1

x=y=0

A1,A2,v=1

0

A1,A2,v=1

x=y=1

A1,A2,v=1

1

A1,B2,v=2

A1,B2,v=2

0

y=0

A1,B2,v=2

0

A1,B2,v=2

0

y=0

A1,B2,v=2

0

1

A1,CS2,v=2

A1,B2,v=2

1

A1,B2,v=2

y=1

1

B1,CS2,v=1

A1,CS2,v=2

1

CS1,CS2,v=1

No further behaviour possible!!

slide46
Reachable part

of region graph

Properties

roughly speaking
Roughly speaking....

Model checking a timed automata

against a TCTL-formula amounts to

model checking its region graph

against a CTL-formula

problem to be solved
Problem to be solved

Model Checking TCTL is PSPACE-hard

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