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System Modeling and
Simulation
TELCOM 2120
Network Performance
Joseph Kabara
Telecommunications Program
University of Pittsburgh
Spring 2008, notes5
TELCOM 2120: Network Performance
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Simulation
•
Simulation:
the process of designing a mathematical or logical
model of a system then conducting experiments with the model to
describe, explain and
predict
the behavior of the system
•
Strengths
– Allows details to be included.
– Can compare alternate system designs.
– Can control time scale.
– Existing system not required
•
Weaknesses
– Difficult to generalize results.
– Difficult to consider all cases/parameter values.
– Hard to determine sensitivity.
– Time to develop and execute simulation.
– Effort to validate model and analyze output data.
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TELCOM 2120: Network Performance
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System Definitions
•
System Definitions
1. Parameters – quantities that are fixed or can be controlled
2. Variables – quantities that are determined by functional relationships
3. State Variables – the minimum set of
variables to completely describe
a system at
a point in time
•
Systems properties
1. Static – state variables are independent of time
2. Dynamic
 state variables are a function of time
1. Continuous time – states are continuous function of time
2.
Discrete time
 states only defined at certain time points
3. Combined – system contains both continuous and discrete
variables
3. Continuous State – state variables can take on values from a
continuous range
4. Discrete state – state variables can only take on values from a discrete
range
5. Deterministic
 state variable can be predicted with certainty
6. Stochastic – state variables include some source of randomness
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TELCOM 2120: Network Performance
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System Definitions
•
Computer system and communication
networks are dynamic continuous
time, discrete state, stochastic
systems.
•
Note that states can only take values
from a discrete range
and are
constants between changes.
•
Point in time where the state changes
– an “event time’’
•
What causes the state change is
called an ``event’’
– For example
 arrival of a packet
to a router queue
•
Such systems are called Discrete
Event Systems
event times
Spring 2008, notes5
TELCOM 2120: Network Performance
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Simulating Discrete Event Systems
1.
States
Collection of variables necessary to characterize the system at any time
point
2.
Entities
objects processed
in simulation – for example packets
or phone calls
3.
Attributes
characteristics of entities (e.g., packet length, type and destination)
4.
Resources
Substances/items that the entities engage in or use (e.g., buffer space at
router, tokens in
a FDDI network, bandwidth on a link)
5.
Activities
Duration of time of whose length
is
known when it begins
For example, transmission time of a packet on a link
6.
Delay
Duration of time of unspecified length
which is not know until it ends
For example – time for a packet to travel from node A to node B in a
network
Spring 2008, notes5
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 Spring '09
 Randomness, Network performance, Discrete Event Systems

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