Computer Simulation of Networks ECE/CSC 777: Telecommunications Network Design Fall, 2013, Rudra Dutta

Copyright Fall 2013, Rudra Dutta, NCSU 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 2013, Rudra Dutta, NCSU Simulation and Model Image courtesy of GSU, “Hyperphysics” site, Rovio

Copyright Fall 2013, Rudra Dutta, NCSU 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 2013, Rudra Dutta, NCSU 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”

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 Copyright Fall 2013, Rudra Dutta, NCSU S S D D 0s: S sends P1 10s: S sends P2 20s: S sends P3 2s: R rcvs P1

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 Copyright Fall 2013, Rudra Dutta, NCSU S S D D 0s: S sends P1 10s: S sends P2 20s: S sends P3 13s: R rcvs P1+ 11s: S sends P1+ 11s: S rcvs MI 9s: R sends MI 2s: R rcvs P1 12s: R rcvs P2

Copyright Fall 2013, Rudra Dutta, NCSU 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 2013, Rudra Dutta, NCSU 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 2013, Rudra Dutta, NCSU Specification Data Collection and Simulation Analysis Using OPNET The cycle is repeated until we achieve the correct objective

Copyright Fall 2013, Rudra Dutta, NCSU Typical Applications Network (LAN/WAN) performance modeling Network planning R & D in communications architectures and protocols Resource sizing …

Copyright Fall 2013, Rudra Dutta, NCSU 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 2013, Rudra Dutta, NCSU

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 2013, Rudra Dutta, NCSU Creating Models in OPNET (1-b) Corresponds to the network architecture / topology

Copyright Fall 2013, Rudra Dutta, NCSU 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 2013, Rudra Dutta, NCSU Creating Models in OPNET (2-b) Corresponds to the internal structure of devices in the network

Copyright Fall 2013, Rudra Dutta, NCSU 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 2013, Rudra Dutta, NCSU Creating Models in OPNET (3-b)

Copyright Fall 2013, Rudra Dutta, NCSU 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 – Probe editor – Straight from the project editor

Copyright Fall 2013, Rudra Dutta, NCSU Simulation & Analysis Simulation execution – 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