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Chapter 4. TCP/IP Network Simulation. Objectives. Appreciate the role of simulation in performance evaluation of TCP/IP networks Acquire the knowledge needed to conduct steady state simulation Master basic skills for analyzing confidence level Describe types of simulation tools available
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Chapter 4 TCP/IP Network Simulation
Objectives • Appreciate the role of simulation in performance evaluation of TCP/IP networks • Acquire the knowledge needed to conduct steady state simulation • Master basic skills for analyzing confidence level • Describe types of simulation tools available • Familiarize with the capabilities of popular simulation tools
Contents • Why use simulation • Systematic simulation study • Types of simulations • Simulation validation and verification • Confidence level of simulation results • Simulation with self similar traffic • Simulation tools
Why Use Simulation
Why Use Simulation • Predict performance for proposed network • Allow performance evaluation under a wide variety of network conditions • Compare alternative architectures under identical and repeatable conditions • Produce results closer to reality • Validate analytical results
Systematic Simulation Study
Systematic Simulation Study • Pre-software stage • Define problem/objective • Design network model and select fixed parameters • Select performance metrics • Select variable parameters
Systematic Simulation Study (Cont.) • Software stage • Model construction • Simulation configuration • Simulation execution/Data collection • Result presentation
Types of Simulation
Types of simulations • Continuos vs. discrete event • Terminating vs. steady state • Synthetic vs. trace-driven
Steady State • If we are interested in asymptotic behavior of a network system, we cannot use terminating simulations • Must continue until it reaches steady state
Trace-Driven Simulations • Actual network traces can be used as simulation input • Results can be more convincing
Simulation Validation and Verification • Validation: Make sure that the assumptions are realistic • Verification: Make sure that the model implements assumptions correctly • Guidelines to follow • Look for “surprise” in output • Employ analytical modeling • Compare with real network data
Confidence Level • Relative precision formula for 95% confidence (see Eq. 4.8, pp. 84) • Confidence level in terminating simulation • Repeat the entire simulation many times with different random numbers (or seeds) • p105, Fig. 4.4
Confidence Level (cont.) • Confidence level in steady-state simulation • Fixed length simulation • Adaptive length simulation
Self Similar Traffic • Poisson model does not capture the burstiness of TCP/IP traffic • TCP/IP traffic usually exhibits self similar property • Generated by superimposing many ON/OFF sources with Pareto distribution
Classification of Simulation Tools • GPPL: General Purpose Programming Language • PSL: “Plain” Simulation Language • SP: Simulation Package • p110, Fig. 4.7
NS Simulator • Developed by UC Berkeley • Public domain SP • Object-oriented • Written in C++ and object-oriented tcl (Otcl) • Network components are represented by classes
OPNET • Developed by OPNET Technologies Inc. • Commercial SP • Object-oriented • Totally menu-driven package • Built-in model libraries contain most popular protocols and applications • Simulation task made easy
Selecting the Right Tool • Built-in libraries • Credibility • User-Friendliness • Technical support • Level of Details • Resource consumption • Cost
NS vs. OPNET • Both have emerged as de facto “standard” for simulating TCP/IP networks • P143, Table 4.6