1. Computer Simulation of Networks
Rudra Dutta
CSC 401- Fall 2011, Section 001

2. Objective - Performance Study
Direct Measurement
Reactive
Disrupts the user/system, affects the behavior/characteristics
Can be done only on completed running systems
Predictive
Analytical Methods
Useful if the model is available and is computationally efficient
Most systems are complex and require highly complex mathematical models
Usually only steady state can be modeled
Simulation
Give more detail than analytical modeling
Very useful when large design space to be explored
Can study dynamic behavior
Not exact and involves some amount of approximation
Can explore only part of operational space
Halfway approach - some implementation
Copyright Fall 2011, Rudra Dutta, NCSU

3. Image courtesy of GSU, “Hyperphysics” site, Rovio
Simulation and Model
Image courtesy of GSU, “Hyperphysics” site, Rovio
Copyright Fall 2011, Rudra Dutta, NCSU

4. Simulation Programmatic representation of system entities
We know how bits and pieces of the system work algorithmically
Possibly for some bits we know mathematically
Implement these algorithms and let them interact
Two main types of simulation
Discrete event
discrete points in time, using random number generators
Continuous time
State changes occur continuously across time
Packages
E.g. OPNET (commercial), NS-2 (open source), OMNeT++
Levels of detail
E.g. packet level, flow level
Copyright Fall 2011, Rudra Dutta, NCSU

5. Discrete Event Simulation
Useful for speeding up when details are abstracted
Decide what happens first
Many things happen after this that are not modeled in the simulation
E.g. in GBN the next thing after receiving frame is sending ACK
Decide what events are triggered by this event that are modeled by simulation
Arrange in order of time of occurrence
Jump to next event, do the same
Until you run out of events, or have run it for “long enough”
Copyright Fall 2011, Rudra Dutta, NCSU

6. Discrete Event Example
Sender transmits three messages at times 0s, 10s, 20s
The channel takes 2s to propagate
Receiver takes a random time between 1s and 9s to process
Sends back either a “more info” request or an “OK”, alternately
Upon “more info”, sender sends one more message immediately
0s: S sends P1
2s: R rcvs P1
10s: S sends P2
20s: S sends P3
Copyright Fall 2011, Rudra Dutta, NCSU

7. Discrete Event Example
0s: S sends P1
Sender transmits three messages at times 0s, 10s, 20s
The channel takes 2s to propagate
Receiver takes a random time between 1s and 9s to process
Sends back either a “more info” request or an “OK”, alternately
Upon “more info”, sender sends one more message immediately
2s: R rcvs P1
9s: R sends MI
10s: S sends P2
11s: S rcvs MI
11s: S sends P1+
12s: R rcvs P2
13s: R rcvs P1+
20s: S sends P3
Copyright Fall 2011, Rudra Dutta, NCSU

8. Event Processors Each event generates new events
Event generation algorithm is an algorithmic model of the part of the system being simulated
“Callback” handlers or processors
Processing algorithms represent specific entities, e.g. GBN receiver
These can obviously grow quite complex
Usually the bulk of the effort of simulation
Also the problem specific part
The Discrete Event framework is an engine and can be commoditized
Hence the concept of “entity models” that plug into such an engine
Copyright Fall 2011, Rudra Dutta, NCSU

9. Introduction to OPNET A variegated software package
Modeler, IT Guru, SP Guru, …
Modeler: a comprehensive development environment driven from GUI
Features
Object-oriented modeling
Discrete event simulator
Integrated data analysis tool
More scalable and efficient simulation engine
Hundreds of protocol and vendor device models
Flexibility to develop detailed custom models
Extensive online documentation and tutorials - quick overview here
Copyright Fall 2011, Rudra Dutta, NCSU

10. Data Collection and Simulation
Using OPNET
Specification
Data Collection and Simulation
Analysis
The cycle is repeated until we achieve the correct objective
Copyright Fall 2011, Rudra Dutta, NCSU

11. Typical Applications Network (LAN/WAN) performance modeling
Network planning
R & D in communications architectures and protocols
Resource sizing …
Copyright Fall 2011, Rudra Dutta, NCSU

12. Model Specification
Objective - developing a representation of the system
Mirrors the hierarchical structure of real networks/systems/…
Primarily three levels of abstraction
Network Model (highest level)
Entire network, e.g., the entire Internet
Node Model
Individual devices, e.g., computers, routers, servers, …
Process Model (lowest level)
Basic level of functionality
Typically individual protocols
Copyright Fall 2011, Rudra Dutta, NCSU

13. Copyright Fall 2011, Rudra Dutta, NCSU

14. Creating Models in OPNET (1-a)
Project Editor  Network Model
Main work place for creating a network simulation
Where you can :
Create a network model using models from the Standard Model Library (the highest level of abstraction)
Choose statistics to collect
Execute a simulation
View results
Two options
Object Palette (use built-in models)
Build your own nodes
Copyright Fall 2011, Rudra Dutta, NCSU

15. Creating Models in OPNET (1-b)
Corresponds to the network architecture / topology
Copyright Fall 2011, Rudra Dutta, NCSU

16. Creating Models in OPNET (2-a)
Node Editor  Node Model
2nd level of abstraction
Used to define the behavior of each network object (node/system)
Important constituents of node model are
Modules
They model some internal aspect of node behavior
E.g. simple traffic source, processor, …
Packet streams (flow of data)
Connect modules
Two options
Use the library
Build your own process modules
Copyright Fall 2011, Rudra Dutta, NCSU

17. Creating Models in OPNET (2-b)
Corresponds to the internal structure of devices in the network
Copyright Fall 2011, Rudra Dutta, NCSU

18. Creating Models in OPNET (3-a)
Process Editor  Process Model
The lowest level of abstraction
Represented by Finite State Machines (FSMs)
State (icons)
Transitions (lines)
Operations performed in each state or for a transition are described in embedded C/C++ code blocks
Copyright Fall 2011, Rudra Dutta, NCSU

19. Creating Models in OPNET (3-b)
Copyright Fall 2011, Rudra Dutta, NCSU

20. Many Other Editors E.g. link model editor, path editor, … Probe editor
Specify the statistics to be collected during simulation, e.g. delay, throughput, utilization, …
Two types of statistics
Global
Local
Two ways to collect statistics
Straight from the project editor
Copyright Fall 2011, Rudra Dutta, NCSU

21. Simulation & Analysis Simulation execution Analysis
using the “configure simulation” tool, or “advanced configure simulation” tool
Can specify various attributes, simulation time and other details
Analysis
Directly from project editor
No. of ways to analyze the results: get time-average, peak values, etc.
Graphical analysis
Copyright Fall 2011, Rudra Dutta, NCSU