Using ModelSim, Matlab/Simulink and NS for Simulation of...

Fraunhofer InstitutIntegrierte Schaltungen

U. Hatnik, S. Altmann

Fraunhofer Gesellschaft EAS/IIS

SDA 20048. September 2004

Using ModelSim, Matlab/Simulink and NS forSimulation of Distributed Systems

Outline

• Motivation

• Requirements

• Object Oriented Simulation

• Objects and Object Structure

• Open Model Interface

• Object Communication Versions

• Conclusions

Motivation

Analysis of communication systems through abstract network simulation

• Analysis of workload, bottlenecks,

reserves and configurations

• Guarantee of the Quality of Service

• Effects of distributed services

• Development of new protocols

• Error simulation

Server

Network(WAN, LAN)

Clients

z−1 +

1k kk 0 1

Motivation

Detailed simulation of single components of a distributed system

• Development of new soft- and hardware

e.g. network adapter, protocol accelerator,

signal processing algorithms

• Exploration of existing components

e.g. with hardware debugger

• Simplification of the design process

• Validation and test

• Fault diagnostics

Motivation

Network Simulator NS-2:

• Based on abstract models, without real reference data

• Provided with extensive libraries (e.g. protocols, transmission lines)

• Not well suited for circuit simulation (absence of libraries, languages, tools)

VHDL/Verilog Simulator ModelSim:

• Modelling with low abstraction level possible

• Provided with extensive circuit libraries

• Not well suited to simulate communication networks

Motivation

Matlab/Simulink

• Models mainly based on differential and difference equations

• More and more libraries and toolboxes available (e. g. for signal processing)

• Not well suited to simulate circuits or for protocol development

Real system components, e. g. User-Mode Linux:

• If no model available

• If real stimuli data necessary

• For validation and test (comparison of real components and models)

Requirements for a Suitable Simulation Environment

• Combination of models with different abstraction levels

• Less restrictions in terms of modelling languages

• Good extensibility (models, simulation algorithms)

• High flexibility at low complexity of the framework

• Integration of soft- und hardware components

• Distributed simulation

=> Coupling of Simulators

Obj. 2.2Obj. 2.1

Obj. 3.2Obj. 3.1

Obj. 1

Interface

Sim. Algorithm

Object

other Objects

The Object Oriented Approach

• Partitioning of the system

• Object is equivalent to subsystem

• Object = Model + Simulator + Interface

• Object can use further objects

• Object encapsules implementation details

=> Simple replacement of objects

=> Object implementation can be changed easily

=> Integration of real soft- and hardware possible

Top Level View

Network Model

Server

Network(WAN, LAN)

Clients

Server Models

Client Models

The Network Simulator NS Version 2

• LAN, WAN, mobile- and satellit networks

• Simulator- and model implementation with oTcl and C++

• Library and examples (protocols, network types etc.)

• Dynamic scenarios

• Animation tool NAM

• Free software, source code available

The Network Simulator NS Version 2

NetworkSimulatorNS-2

Top Level System Model

Top Level Object

Interface

NetworkSimulator

Detailed Simulation of a single Component

Network Model

ModelSim Object

VHDL / VerilogSimulatorModelSim

hardwarecomponent

ModelSim Object

Interface

VHDL / VerilogSimulatorModelSim

hardwarecomponent

Matlab/Simulink Object

Matlab/Simulink

signal processing

Matlab/Simulink Object

Matlab/Simulink

signal processing

Interface

Applications

User Mode LinuxSystem 1

Virtual Network Module

Applications

Linux System

User Mode Linux Object

Interface

Applications

Virtual Network Module

Applications

Linux System

Object StructureInterface

Object Structure

Interface

A2ModelSim HardwareComponent

Interface

Object Structure

Interface

System

Applications

User Mode LinuxSystems

Software

Object Structure

Interface

A2ModelSim

Interface

Matlab/Simulink Signal Processing

Hardware

Algorithm

Component

Interface

System

Applications

Software

Object Structure

Interface

A2ModelSim

Interface

Hardware

Algorithm

Component

Interface

System

Applications

Software

Interface

System Hardware FPGA

Object Structure

Interface

A2ModelSim

Interface

Hardware

Algorithm

Component

Interface

System

Applications

Software

Interface

System Hardware FPGA

Open Model Interface (OMI)

• IEEE standard

• Object oriented approach

• Open and independent interface

• Dynamic simulation control

• Intellectual property (IP) protection

• Visibility of intern signals

• Licence and version management

• Flexible model creation

• Model query functions

Properties:

Basic Structure of the Open Model Interface

Model Manager

OMILibrary

Model 1

Model 2

Instance 1 Instance 2 Instance 3

Application

Model Manager

OMILibrary

Model 1

Model 2

Instance 1 Instance 2 Instance 3

Interface

Model Manager

System

Applications

SoftwareMatlab/Simulink Signal Processing

Algorithm

Interface

Library

Model 1

Model 2

Model Manager

System

Applications

Algorithm

Interface

Model Manager

TCP/IP-Sockets

System

Applications

Algorithm

Interface

(PVM, CORBA, HLA)

Object Communication Versions

• TCP/IP-Sockets(high effort, dependent on platform)

• Parallel Virtual Machine (PVM)(low effort, independent of platform)

• High Level Architecture (HLA)(developed especially for simulator coupling, mechanism for synchronisation)

• Common Object Request Broker Architecture (CORBA)(transparent coupling of distributed objects, client server architectur)

Conclusions

• Simulation of distributed systems via simulator coupling

=> Combination of suitable simulators (abstraction level,

modelling language, available libraries)

• OOS approach (autonomous objects, optimale adaption on requirements,

integration of real soft- and hardware components possible)

• OMI (interface standard for object coupling)

• Object communication via TCP/IP-Sockets

=> distributed simulation is easily possible

• Further coupling methods possible (PVM, CORBA, HLA)

• Very flexible and user comfortable simulation environment

Using ModelSim, Matlab/Simulink and NS for Simulation of...

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