Background of Wireless Communication Student Presentations and Projects Wireless Communication Technology Wireless Networking and Mobile IP Wireless Local Area Networks Wireless Communication : LAB 1 Introduction To Simulation Software

Simulation  A simulation is an imitation of some real thing, state of affairs, or process.  The act of simulating something generally require representing certain key characteristics or behaviors of a selected physical or abstract system.  Simulation is used in many contexts, including the modeling of natural systems or human systems in order to gain insight into their functioning.

Simulation (Contd.)  Other contexts of simulation include simulation of technology for performance optimization, safety engineering, testing, training and education.  Simulation can be used to show the eventual real effects of alternative conditions and courses of action.  This provides real like results without having to perform the actual experimentations in real world.

Why Simulation?  Understand the manufacturing system  Inventory issues  Capacity  Flow  Analyze the situation  What is important?  Why is it important?  Create and test new ideas  Quick and dirty analyses

How to do Simulation?  Investigate the situation  Plan the project  Collect data  Build a conceptual model  Fit distributions to data  Validate  Implement the model in software  Verify  Build many different solutions (answers)  Test the solutions and choose the best answer

Advantages of Simulation  Cost Effective  Some open-source software available  Some packages have entry-level pricing  Expensive packages may be worth it  Easy to do  Specialization = Ease  Fast to complete  Specialized packages are fastest  Easy to communicate the solution  Animation, custom reports and graphics

What’s new in Simulation?  3D animation  Ultra-realistic imaging  Easy integration with popular languages  C#, C++, VB, Access, VBA, Excel, Visio  Optimization of designs (OptQuest)  Automated output analysis  Custom Reports (Crystal Reports)  Automated input analysis (Stat::Fit, ExpertFit)  Specialized modeling packages

3D Animation FlexSim AutoMod Arena

Ultra-realism

Language integration  Excel (reports)  Access (data retrieval)  VBA (integration with Office tools)  VB  C#  C++  Visio (process modeling)

Visio integration  Build the process in Visio  Use the simulation engine to evaluate it Witness Arena ProModel

Custom Reporting Crystal Reports Arena FlexSim Witness  The output is integrated with Crystal Reports  Customized reports can be built quickly  Output can also be sent to Excel for further analysis

Automated Input Analysis ExpertFit Stat::Fit  Data is collected  Data is imported into ExpertFit or Stat::Fit  Probability distributions are automatically fit to the data (family and parameters)  The distribution representations are customized for the simulation package

Specialized Modelers  Computer Networks  Call Centers  Hospitals  Work Flow  Traffic Flow  Manufacturing

Discrete Event Simulation Overview  In discrete event simulation, the operation of a system is represented as a chronological sequence of events.discretesimulationsystemevents  Each event occurs at an instant in time and marks a change of state in the system.  For example, if an elevator is simulated, an event could be "level 6 button pressed", with the resulting system state of "lift moving" and eventually (unless one chooses to simulate the failure of the lift) "lift at level 6".

Discrete Event Simulation (contd.)  A common exercise in learning how to build discrete event simulations is to model a queue, such as customers arriving at a bank to be served by a teller.  In this example, the system entities are CUSTOMER-QUEUE and TELLERS.  The system events are CUSTOMER-ARRIVAL and CUSTOMER-DEPARTURE.

Discrete Event Simulation (contd.)  The system states, which are changed by these events, are NUMBER-OF- CUSTOMERS-IN-THE-QUEUE (an integer from 0 to n ) and TELLER-STATUS (busy or idle).  The random variables that need to be characterized to model this system stochastically are CUSTOMER- INTERARRIVAL-TIME and TELLER-SERVICE- TIME.random variables

Discrete Event Simulation Mechanisms  A number of mechanisms have been proposed for carrying out discrete event simulation, among them are:  event-based,  activity-based,  process-based  and three-phase approach

Discrete Event Simulation Mechanisms (contd.)  The three-phase approach is used by a number of commercial simulation software packages, but from the user's point of view, the specifics of the underlying simulation method are generally hidden.  Three-phase maintains a distinct separation of state (dependent) and time (bound) conditions.  All state conditions are executed before the advance of time to the next bound condition.

Available Simulation Software

Animate  This simulation package is more targeted for the business user; however it can be used in academia as a teaching tool.  It’s got good graphical user interface, but the simulation process doesn’t show the concepts pretty clearly and lacks flexibility, i.e. additions and deletions not supported.  License required.

Cnet  A discrete-event network simulator enabling experimentation with various data-link layers, network layer, routing and transport layer protocols.  It is widely used in undergraduate computer networking courses by students worldwide.  It has a graphical interface showing simulated packages travelling in a virtual network environment.

GloMoSim  GloMoSim is a scalable simulation environment for wired and wireless network systems.  It employs parallel discrete-event simulation capability provided by Parsec  Currently supports protocols for a purely wireless network, although, the developers are anticipating adding functionality to simulate wired as well as hybrid networks.  Easy to operate but slow in operations, available to academic institutions for research purposes.

GTNetS  The Georgia Tech Network Simulator (GTNetS) is a full-featured network simulation environment for studying the behavior of moderate to large scale networks  GTNetS creates simulation environment that is structured much like actual networks are structured and has clear and distinct separation of protocol stack layers.  Freely available.

INSANE  An Internet Simulated ATM Networking Environment for testing various IP-over-ATM algorithms with realistic traffic loads derived from empirical traffic measurements.  IP, TCP, and UDP are the supported protocols.  Written in C++  Freely available.  Only runs on Unix.

Macromedia Captive  This application records a user’s action and produces a video clip of all the activities.  A very effective technique for teaching and training end-users.  Unfortunately, this application isn’t useful for simulation as it fails to show detail information about the internal operations of the system.

NCTUns  A high-fidelity and extensible network simulator/emulator capable of simulating various protocols used in both wired and wireless IP networks  It can also be used as an emulator by using Linux TCP/IP protocol stack to generate high-fidelity simulation results  Its core technology is based on the novel kernel re-entering methodology  NCTUns is commercialized, therefore not freely available to academia

NetSim  Netsim provides a very detailed simulation of single segment bus networks running the Ethernet (CSMA/CD) protocol.  Finite population networks are modeled, with the simulation taking station position into account in determining the duration of collisions and the beginning of the backoff period at each station involved in a collision.  An experiment description file allows the user to set a wide variety of parameters for a simulation run, including very flexible traffic generation processes for individual hosts on the simulated network. Freely available.

NetSim++  It is used to measurement performance in existing or future communications networks with wide ranges of conditions for the analysis and simulation of queuing systems.

Ns2 *  A discrete event simulator targeted at network research.  It provides substantial simulation support of TCP, routing and multicast protocols over wired and wireless networks.  The good thing about Ns2 is its flexibility, it allows specification of almost everything e.g. bandwidth, queuing model, topology etc.  Ns2, however, involves programming Tcl scripts to invoke the simulation process, which can be hard to understand by novice users.  Available on Unix and Windows.

OMNeT++ *  A component-based modular and open- architecture simulation environment with strong GUI support and an embeddable simulation kernel.  It is easy to use for modeling communication protocols, computer networks, traffic modeling, multi-processors and distributed systems, etc.  OMNeT++ also supports animation and interactive execution.  Freely distributed under academic public license.

OPNET Modeler  A combination of predictive modeling and comprehensive understanding of networking technologies to enable users to design, deploy, and manage network infrastructure, network equipment, and networked applications.  OPNET Modeler is a development environment, allowing the design and study of communication networks, devices, protocols, and other applications.  However, there are limitations to the use of OPNET, the simulation process only shows the behavior of the network instead of the actual processes and also limited to devices on the simulation package.  There are downloadable streamline versions for use on windows platforms.

Performance Prophet  Used for modeling and simulating high performance computing systems by predicting the execution behavior of the application model on cluster and grid architectures.  The package doesn’t show actual processes.

QualNet  QualNet is claimed to be the fastest real-time traffic modelling tool for wireless and wired networks  The Animator allows graphically design of network models from a wide library of components to describe the network behaviour.  Windows and Linux demo versions available.

Real 5.0  A network simulator originally intended for studying the dynamic behavior of flow and congestion control schemes in packet- switched data networks.  Real 5.0 simulates flow control algorithms such as TCP and various queuing disciplines. Written in C.  Uses NeST simulator and freely available  A license form must be filled  Operates only on Unix.

S3  Scalable Self-Organizing Simulation Software for simulating the Internet.  Freely available for download  For Unix and Windows

Simured  Simured is a simulation tool for computer cluster traffic.  Open source.  For Unix and Windows systems.

SWANS  SWANS is a scalable wireless network simulator organized as independent software components that can be composed to form complete wireless network or sensor network configurations.  Its capabilities are similar to ns2 and GloMoSim,  SWANS is able to simulate much larger networks.  It is designed to achieve high simulation throughput, saving memory, and running standard Java network applications over simulated networks.

Traffic 2.0  A simulation product designed to solve complex call-centre modeling problems  It can also be applied to any other queuing problem.  It has an easy to use graphical interface.  It runs on Windows.

Simulation Software used in this course  NS2 ns-allinone-2.32 releasens-allinone-2.32 release  OMNeT++  LabVIEW by

Conclusion  Many new features to help with:  Modeling: language, Visio, animation  Analysis: automated input and output  Communications: 3D animation and virtual reality  Experimentation: optimizers  Simulation models are becoming more powerful, easier to build, and capable of representing much more complex systems  Open source simulation software are improving in terms of features,ease of use and availability of libraries  We will use NS2, OMNeT++ and LabVIEW

Next Lab  Installation of NS2 on Windows  All Lecture and Lab slides will be available on  Student may login as:  User: guest1  Password: guest1