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Octopus: document handling
Document handling:three modeling approaches
Marc Voorhoeve
Venkatesh Kannan
TUE
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Octopus: document handling
Octopus project
Broker: EESI
Industry partner: Océ
Researchers:NijmegenTUE - Electrical EngineeringTUE - Computer Science
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Octopus: document handlingData path:concurrent job execution
scan
control
retrieve
ImageProcessing
store
IP1 IP2
resources
user
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Engineering decisions:- resource capacity- scheduling rules
Octopus aim:Engineering support
Frameworks:- TA (Timed Automata)- SDF (Synchronous Data Flow)- CPN (Colored Petri nets)
SimulationState spaceexploration
Approaches
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Timed automata:labeled transition system with clock variables,that can be set and tested.
states,actions (maybe silent),clock assignments,clock conditions.
idle busy
recover
start?
0:x0:x
etxrtx
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Kind of merge with synchronization of clocks.
idle busy
recover
start?
0:x
0:xetxrtx
s0 s1start! s2start!
0:y
(idle,s0) (busy,s1) (recover,s1) (idle,s1) (busy,s1) (recover,s1) (idle,s2)
0,0 yx ety re tty )(2 re tty
Temporal predicates (CTL) can be assessed,e.g. existence of execution path with duration D.
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CPN (colored Petri nets):Petri net with arc inscriptions, firing conditionsand subnet hierarchy.Eager firing.
idle busy
recover
start
etx @
xx
xx
( )
rt@)(
start s0
s1
s2
a
b
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SDF:action-based,Petri net subclass(marked graph)
Firing delaysfast optimalschedule computation
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Special challenge: modeling USB storage/retrieval.
unidirectional capacity: H, bidirectional capacity: Lcapacities L,H in MB/sec satisfying L < H < 2L.
Suppose 3H upstream; after 1 sec L downstreamtiming diagram:
0 1 2 3 3+(H-L)/H
HL
2L
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USB model:hybrid system.
Discrete approximation in TA possible.Exact CPN model by data manipulation.SDF model is still under construction.
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Experiences so far:- coordination via regular meetings- agreement on parameters of common model- mutual validation has been achieved (despite several difficulties)
Next stages:- validation with current project - exploration of engineering alternatives- adaptivity?
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CPN tradeoff: structure in net vs. color
more structurevisual modellow-levelless flexible
structure in coloropaquehigh-levelflexibility
TA tradeoff: model vs. predicate
constraints in modelsmaller state spacemore models
constraints in predicatelarger state spaceless models (flexibility)
Some difficulties were caused by the solutionsthat the various frameworks allow.
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CPN model therefore opts for flexibility.
Other difficulties caused by unstable requirements.
color set JOB: sequence of tasks.
a
b
[a,b]
x != [ ]
x tail(x)
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jobQ
JOB
scanner scanIP IP1 IP2 USB printIP
startedJob
JOB
schedulerJobGenerator
newJob
JOB
memory
INT
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start do
free
jobQ
JOB
startedJob
JOB
compInfo
paperInfo
end
parameters
structure of scanner, scanIP, IP1, IP2, printIP
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job in join
trigger
USBjobList
updatejobout
Job Rate LastUpdateTime
JOB JOB
structure of USB subnet
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0 1 2 3 3+x
HL
2L
Depicted USB scenario:
0 U H 0 31 U L 1 3+x
D L 1 22 U H 23 U H 33+x -
time job rate last_update_time trigger
x=(H-L)/H
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TA, SDF:find "optimal" schedulewithin state spacefor a given job sequence
CPN:nondeterministiceager execution
Mutual validation of models:- remove freedom- model within intersection- compare generated schedules (traces)
Mutual validation: do the models match?
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Modeling power vs. analysis options:
CPN: most power, least analyzable.SDF: least power, analysis limited but fastTA: wide range of analysis options danger of state space explosion
Possible developments for Océ:- competition- cooperation
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Conclusions:
Combination of formal frameworksinteresting, but time-consuming.
More time needed for assessment.
Questions?