7. Network Simulation Network Performance and Quality of Service

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 RQ122

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 Simulation can incorporate more details than analytical modeling, thus produce results closer to reality Validate analytical results RQ123

Systematic Simulation Study Pre-software stage  Define problem/objective  Design network model and select fixed parameters  Select performance metrics  Select variable parameters RQ124

Systematic Simulation Study Software stage  Model construction  Simulation configuration  Simulation execution/Data collection  Result presentation RQ125

Systematic Simulation Study (Cont.) Software stage  Model construction  Simulation configuration  Simulation execution/Data collection  Result presentation RQ126

Types of simulations RQ127  Continuous vs. discrete event  Terminating vs. steady state  Synthetic vs. trace-driven

Continuous vs. discrete event The state of the system model can be …  continuous (concentration of substance in chemical system)  discrete (queues of packets in packet switching system) A discrete event simulation (DES) uses a discrete state model of a system Each event has an associated time value indicating the time to execute the event RQ128

Terminating vs. steady state Terminating simulation is to study network system for a well-defined period of time or number of events. If we are interested in steady-state behaviour of a network system, we cannot use terminating simulations Must continue until it reaches steady state RQ129

Synthetic vs. trace-driven In many simulations, input traffic is synthetically generated using random traffic generators. Actual network traces can be used as simulation input Results can be more convincing RQ1210

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 RQ1211

Confidence Level Relative precision formula for 95% confidence Confidence level in terminating simulation  Repeat the entire simulation many times with different random numbers (or seeds) RQ1212

Confidence Level (cont.) Confidence level in steady-state simulation  Fixed length simulation  Adaptive length simulation RQ1213

Self Similar Traffic RQ1214  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 RQ1215

Network simulators Commercial  OPNET  QualNet Open Source  NS2  NS3  OMNeT++  SSFNet  J-Sim RQ1216

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 RQ1217

OPNET Lot of component library with source code Object-oriented modeling Hierarchical modeling environment Scalable wireless simulations support Customizable wireless modeling Discrete Event, Hybrid, and Analytical simulation 32-bit and 64-bit parallel simulation kernel Realistic Application Modeling and Analysis Integrated, GUI-based debugging and analysis Open interface for integrating external component libraries RQ1218

OPNET RQ1219

OPNET Platform Supported OPNET Modeler  Microsoft Windows (32 and 64 bit)  Red Hat Enterprise Linux  Fedora Linux OPNET IT Guru (Academic Edition)  Microsoft Windows RQ1220

NS-2 Simulator Discrete Event Simulator Packet level Modeling Network protocols  Collection of Various protocols at multiple layers TCP(reno, tahoe, vegas, sack) MAC(802.11, 802.3, TDMA) Ad-hoc Routing (DSDV, DSR, AODV, TORA) Sensor Network (diffusion, gaf) Multicast protocols, Satellite protocols, and many others RQ1221

NS-2 Simulator Object-oriented Written in C++ and object-oriented tcl (Otcl) Network components are represented by classes From the user’s perspective, NS−2 is an OTcl interpreter that takes an OTcl script as input and produces a trace file as output. RQ1222

NS-2 Platforms supported Most UNIX and UNIX-like systems  FreeBSD  Linux  Solaris Windows  Cygwin required  Some work, some doesn’t RQ1223

OMNET++ OMNeT++ is a component-based, modular and open-architecture discrete event network simulator. OMNeT++ represents a framework approach  Specific application areas are catered by various simulation models and frameworks, most of them open source.  These models are developed completely independently of OMNeT++, and follow their own release cycles. RQ1224

OMNET++ Frameworks Partial list of OMNeT++-based network simulators and simulation frameworks:  Mobility Framework -- for mobile and wireless simulations  INET Framework -- for wired and wireless TCP/IP based simulations  Castalia -- for wireless sensor networks  MiXiM -- for mobile and wireless simulations More specialized, OMNeT++-based simulators:  OverSim -- for overlay and peer-to-peer networks (INET-based)  NesCT -- for TinyOS simulations  Consensus Positif and MAC Simulator -- for sensor networks  SimSANs -- for storage area networks  CDNSim -- for content distribution networks  X-Simulator -- for testing synchronization protocols RQ1225

OMNET++ RQ1226

OMNET++ Platform Supported Microsoft Windows Linux Mac OS X other Unix-like systems RQ1227

Important issues in a discrete event simulation environment Pseudorandom generators Flexibility Programming model Model management Support for hierarchical models Debugging, tracing, and experiment specifications Documentation Large scale simulation Parallel simulation RQ1228

Selecting the Right Tool Built-in libraries Credibility User-Friendliness Technical support Level of Details Resource consumption Cost RQ1229