Chapter 4 DEVS Models for Processing and Coordinating Workflow

1
Chapter 4DEVS Models for Processing and
Coordinating Workflow

• Sending/Receiving/Interpreting Messages
• Processor Models
• Workflow experimental frame components
• Work Flow Coupled Models
• Experimental Frame for Workflow Performance
  Measurement
• Hierarchical Model Construction
• Workflow Coordinator Models
• Workflow Architecture Models
• Performance of Simple Workflow Architectures

2
Sending/Receiving/Interpreting Messages how to
use casting to receive instances of arbitrary
entity subclasses
SimpArc .procQ
coupled model
entity
in
out
A
B
doubleEnt
doubletEnt(double)
double
double
getv() ? double
coupling (A,out,A,in)
public message out( ) message m new
message() m.add( makeContent("out", new
doubleEnt(1.2)) return m
in
out
cast
message
doubleEnt
add
p
getv()
val
doubleEnt
deltext(double e,message) x)if
(somethingOnPort(x,"in") entity val
getEntityOnPort(x,"in") doubleEnt f
(doubleEnt)val double v f.getv()
v
content
double
casting the received entity down to the doubleEnt
subclass
3
Sending/Receiving/Interpreting Messages
(contd) multiple copies of an object are needed
to avoid hard-to-find dependencies.
SimpArc .procQ
coupled model
entity
in
out
A
B
job

• job(procTime)
• update(e)
• procTime e
• copy() return new
• job(procTime)

job
job
coupling (A,out,A,in)
This instance of job is now shared in common by
both A and B if either makes a change to its
state, then the other will also be subject to
it. For example, if B does
job.update(10) then the instance at A will be
similarly altered. This can lead to mysterious
effects (similar to quantum entanglement) where
components of a model can influence each other
outside of their interface couplings. It is
difficult to trace this kind of non-modularity.
Suppose A sends its instance of job directly to
B public message out( ) message m new
message() m.add( makeContent("out", job) return
m
The right way B stores a copy of its
input deltext(double e,message) x) if
(somethingOnPort(x,"in)) job temp
getEntityOnPort(x,"in") myJob
temp.copy() where copy() is a method you define
to create a new instance of job and give it
values of an existing one.
out
and B stores it as its instance deltext(double
e,message) x) if (somethingOnPort(x,"in")) myJob
getEntityOnPort(x,"in")
The cure is simple create a new instance as a
local copy of an entity if it is to be altered
(this happens automatically when using toString()
and toObject(), see chap. 12)
4
Processor Models
SimpArc .proc
SimpArc .procQ
SimpArc .priorityQ
SimpArc job
5
Processor with queue illustrating how to process
a bag of inputs (multiple concurrent events)
accumulate the inputs on port in into the queue
public class procQ extends proc protected Queue
q public procQ(String name,
double procTime ) super(name,procTime) q
new Queue()
public void deltext(double e, message x)
Continue(e) if (phaseIs("passive")) for
(int i0 ilt x.size() i) if
(messageOnPort(x, "in", i))
q.add(x.getValOnPort("in", i))
holdIn("busy", procTime) job
(entity)q.first() else if
(phaseIs("busy")) for (int i0 ilt
x.size()i) if (messageOnPort(x, "in",
i)) entity jb x.getValOnPort("in",
i) q.add(jb)
class Queue is a container with FIFO discipline
this makes sure the processed job is the one
at the front
public void deltint( ) q.remove() if(!q.isEmpty
()) job (entity)q.first() holdIn("busy",
procTime) else passivate()
remove the job at the front that was just finished
SimpArc .procQ
GenCol .Queue
6
Workflow experimental frame components

• To compute the performance measures, the
  transducer, places job-ids that arrive at its
  'ariv input port on its arrived-list together
  paired with their arrival times.When, and if, the
  job-id also appears at the 'solved input port,
  the transducer places it on the solved-list and
  also computes its turnaround time. it maintains
  its own local clock to measure arrival and
  turnaround times.
• In transd, an internal transition is used only to
  cause an output at the
• end of the observation interval. In a more
  general experimental frame, the role of
  terminating the simulation run would be handled
  by a component
• called an acceptor.

SimpArc genr
SimpArc genrRand
SimpArc transd

• The transducer measures two performance indexes
  of interest for work flow the throughput and
  average turnaround time of jobs in a simulation
  run.
• throughput is the average rate of job
  departures from the architecture,
• estimated by the number of jobs processed during
  the observation interval,
• divided by the length of the interval.
• A job's turnaround time is the length of time
  between its arrival to the processor and its
  departure from it as a completed job.
• For the simple processor, the turnaround time is
  the same as the processing time. (For more
  complex architectures, this relationship is not
  necessarily true as we shall see.).

generator is an autonomous model, (its behavior
is self induced by recurring internal events)
hence, it does not need an external transition
function To dictate its response to external
input events. The added an input ports start
and stop when stimulated, start and stop the
generation of outputs.
7
Work Flow Coupled Models
SimpArc .pipeSimple
SimpArc netSwitch
SimpArc gpt
SimpArc ef
SimpArc efp
8
Basic Workflow Coupled Model generator,
processor, transducer
SimpArc gpt
9
Experimental Frame for Workflow Performance
Measurement
SimpArc ef

• Output lines may diverge to indicate the
  occurrence of simultaneous events. When genr
  sends out a job identifier on port out, it
  goes at the same clock time, both to the ariv
  port of transd and port out of ef, hence
  eventually to some processor model.
• Input lines may converge, i.e., two or more
  source ports connected to the same destination
  port, can occur. Bags represent the collection
  of inputs that arrive simultaneously at a
  component.

• Instances of the classes genr and transd are
  coupled together to form the experimental frame,
  ef.
• The input port in of ef is for receiving
  solved jobs which are sent to the solved input
  port of transd via the external input coupling.
  
• There are two output ports out, which
  transmits job identifiers sent to it by genr,
  and 'result which transmits the performance
  measures computed by transd. External output
  couplings bring about both these transmissions.
• There are two internal couplings
• the output port out of genr sends job
  identifiers to the 'ariv port of transd
• the output port out of transd which couples to
  the 'stop input port of genr.

10
Hierarchical Model Construction
SimpArc efp
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Example Flat Coupled Model
SimpArc gpt
gpt
start
start
out
generator (genr)
processor (proc)
out
in
stop
out
arrived
transducer (transd)
out
solved
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Experimental Frame/Model Modularity
SimpArc efp
efP
ef
start
start
start
out
out
generator (genr)
processor (proc)
out
in
stop
out
arrived
transducer (transd)
out
out
solved
solved
13
Hierarchical Coupled Model
SimpArc efp
efP
ef
start
start
Processor With Queue (procQ)
out
out
in
out
out
solved
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Hierarchical Models and Experimental Frame
Modularity in DEVSJAVA
Create EF
ef.setBlackBox(true)
m.setBlackBox (true)
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Workflow Coordinator Models
public class Coord extends proc public
Coord(String name) super(name,1)
inports.add("setup") inports.add("x")
outports.add("y") public void initialize()
passivate() super.initialize()
protected void add_procs(devs p) //use devs
for signature System.out.println("Default in
Coord is being used")
Coord
SimpArc divideCoord
SimpArc pipeCoord
divide Coord
pipe Coord
multi Server Coord
SimpArc multiServerCoord
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Workflow Architecture Models
SimpArc DandC3
SimpArc pipeLine
SimpArc multiServer
17
Performance of Simple Workflow Architectures
SimpArc .proc
SimpArc multiServer
SimpArc pipeline
SimpArc DandC3
Average turnaround time and maximum throughput as
a function of processing time