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Updateable Simulation of Communication Networks

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Reduces the time to complete multiple execution ... iii. In cloning ... cloned once for each branch thus sharing all the computation before the cloning point. ... – PowerPoint PPT presentation

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Title: Updateable Simulation of Communication Networks


1
Updateable Simulation of Communication Networks
  • Steve L. Ferenci,
  • Richard M. Fujimoto, Ph.D,
  • Mostafa H. Ammar, Ph.D,
  • Kalyana Perumalla, Ph.D,
  • George F. Riley, Ph.D
  • Presented By
  • Resty Budodi
  • April 29, 2003.

2
Outline
  • Introduction
  • Shared Computation
  • Incremental simulation
  • Event Reuse
  • Event Composition Computations
  • Summary

3
Introduction
  • What is updateable simulation?
  • A technique that updates the results of a
    prior simulation run rather than re-execute the
    entire simulation.
  • Why updates?
  • Reduces the time to complete multiple
    execution of a discrete event simulation program
    if there is much similarity among runs.

4
Introduction
  • Why not Time Warp?
  • Optimization such as lazy cancellation and
    lazy re-evaluation can be applied. However, there
    are many instances where this approach will
    result in an excessive amount of re-computation,
    and sometimes might cause a roll back to the
    beginning. Thus, Time Warp is not sufficient in
    many application.

5
Why not Time Warp
  • For example, consider a communication network
    simulation where the model changes involve
    modifying the size of the message buffers in each
    switch. Simply applying Time warp will cause the
    entire simulation to be rolled back to the
    beginning.

6
Creating updateable simulation
  • An updateable simulation consists of two phases
  • Initial/primary phase
  • This is an execution of some base-line
    simulation.
  • Update phase
  • Apply an update transformation to the initial
    state to produce the next simulation, the
    initial state of the new simulation. These two
    simulations will have similar computation
    histories.

7
Why Updates
  • Computational savings
  • -Maintaining a time-stamp ordered (the events
    from the primary execution are already in time
    stamp order and do not need to be reordered).
  • -Since events are being used, cost of creating
    and scheduling new events can be saved.
  • -Process a composed event that produce the same
    results more quickly.

8
Shared Computation
  • Use in on-line simulation application.
  • For example
  • i. The standard clock technique
  • An implementation of a single clock multiple
    systems simulation. Certain computations among
    executions of the simulations are shared under
    the assumption that the time stamp assigned to
    events remains the same across the different runs.

9
Shared Computation continue
  • ii. Splitting
  • -A technique used in rare-event simulation,
    splits the simulation at a point just before the
    rare-event occurs and create copies of the
    simulation to increase the number of hits on the
    rare event.

10
Shared continue
  • iii. In cloning
  • At the decision point the simulation is
    cloned once for each branch thus sharing all the
    computation before the cloning point.

11
Incremental simulation
  • Incremental simulation only simulates the
    portion of the circuit that has been modified,
    reusing the rest of previously completed
    simulation.

12
Event Reuse
  • Identifies when an event from the primary phase
    can be reused.
  • Key Point
  • If an event occurs in both the primary and
    update phase, and that event schedules the
    same new event (s) in the update phase that were
    scheduled in the primary phase, the event is said
    to be re-useable. New events need not be
    re-created and re-scheduled for re-useable
    events.

13
Updateable simulation algorithm (Reuse function)
  • The following function determine if the current
    state of the simulation in the update phase is
    sufficiently similar to the corresponding state
    during the primary phase to allow the event to be
    reused.

14
ATM multiplexer algorithm that only tests one
event at a time (reuse function)
  • R1(Sj, Ew)
  • BC Buffer Capacity of Sj
  • BO Buffer Occupancy of Sj
  • E top of Ew, Sj is the state in the primary
    phase before e is executed (if e is in E)
  • /state logged from primary phase/
  • BC Buffer Capacity of Sj
  • BO Buffer Occupancy of Sj
  • if (e not in E or e is cancelled) then
  • return(0)

15
ATM multiplexer function continue
  • else if (e is an arrival) then
  • if( BOBC and BCltBC) then
  • /arrival now must be dropped/
  • return (0)
  • else if( BOBC and BCltBC) then
  • return(0)
  • /arrival must now be queued/
  • return (0)
  • else
  • return (1)
  • endif
  • else if (e is a departure) then
  • return (1)
  • end if

16
ATM multiplexer function uses number of lost
packets per k events to test k events for reuse
  • Rr (Sj, Ew)
  • None of the first k events of Ew is new
  • None of the first k events has been cancelled
  • Lnumber of losses over next k events
  • if (BC gt BO BO and L0)then
  • reuse
  • else
  • do not reuse

17
Event Composition
  • The idea is to determine when a set of events
    could be guaranteed to schedule the same events
    during the update phase as they did in the
    primary phase.
  • Transform the state of the simulation in the
    update phase to a new state to reflect processing
    the events that could be reused.

18
Summary
  • The basic idea in an updateable simulation is to
    update a previously completed simulation run,
    rather than re-execute the simulation from
    scratch.
  • Update will reduce the time to complete multiple
    executions of a discrete event simulation
    program.
  • Multiple simulations runs may share a
    considerable amount of computation and reuse this
    computation will provide a speedup.
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