basic definitions of systems

7/28/2019 Basic Definitions of Systems

1/32


2/32

2

OBJECTIVES / CONTENTS

Saad Haj Bakry

Systems, Models & Simulation: Basic Definitions

SYSTEMS:

Definitions

Architecture

Examples

System Studies

MODELS:

Types / Definitions

Suggested Work

SIMULATION:

DefinitionsTypes / Steps

Advantages /

Disadvantages

Use


3/32

3

DEFINITION: 1/2

Saad Haj Bakry

Schmidt &

Taylor [2]:

A collection of

entities e.g. people or

machinesthat act

and interacttogether toward the

accomplishment of

some logical end.

Simple

Definition [1]:

An aggregation or

assemblage of

objects joined insome regular

interaction or

interdependence.

SystemsSystems, Models & Simulation: Basic Definitions


4/32

4Saad Haj Bakry

IEEE Computer

Dictionary [4]:A collection of

components

organized toaccomplish aspecific function or

a set of functions.

ISO / IBM [3]:

A collection of

men, machines,

and methods

organized toaccomplish a set

of specific

functions.

DEFINITION: 2/2

SystemsSystems, Models & Simulation: Basic Definitions


5/32

5

CONSIDERING STUDY OBJECTIVES

Saad Haj Bakry

System according toStudy Objectives

Examples

What is meant by theSystem depends on the

objectives of aparticularstudy.

the System for onestudy may be a subset

ofthe System ofanother study

Network Exchange:

All links & total traffic

One two directional link andtwo way traffic.

One directional link with oneway traffic

Systems

Reference 2



6/32

6

SYSTEM ARCHITECTURE

Saad Haj Bakry

System State:function of time

System

Entity

Entity

Attribute

AttributeAttribute

Activity

Activity

Deterministic / Stochastic

EndogenousContinuous / Discrete

Structure

System Environmentboundary

Open

Closed

Exogenous

Systems

Using References 1 & 2



7/327

BASIC COMPONENTS

Saad Haj Bakry

EntityAn object component in the

system

Attribute A property of an entity

ActivityA process that cause changes in

the system

SystemState

Description of system entities,attributes, and activities at any

point in time(relative to Study Objectives)

Systems

Reference 1



8/328

Systems

Saad Haj Bakry

System BoundaryBoundary between the system and

its environment

SystemEnvironment

Changes occurring outside thesystem are said to occur in thesystem environment

EndogenousActivities

Activities occurring within thesystem.

ExogenousActivities

Activities occurring in the systemenvironment, and affect the system

Open System A system with exogenous activities

Closed SystemA system with no exogenous

activities

BOUNDARIES

Reference 1



9/329

CHANGE: 1/2

Systems

Saad Haj Bakry

System Definition Examples

DiscreteVariables

Instantaneouschanges at

separated pointsin time

Digital signals Integer Variables

Number of people

ContinuousVariables

Continuous

change withrespect to time.

Analog Signals

Temperature

Speed

SystemsCombination: Predominantly

(Discrete / Continuous)




10/3210

Systems

Saad Haj Bakry

System Definition Examples

DeterministicActivities

Outcome can bedescribed

completely interms of the input

Systemmonitoring

StochasticActivities

Random:

Occurrence /Outcome

Systemfailures

SystemActivities

Combination: Predominantly

(Deterministic / Stochastic)

CHANGE: 2/2




11/3211

EXAMPLES

Systems

Saad Haj Bakry

SystemExamples

Entities Attributes Activities

E-Mail Messages Length /Priority

Send /Receive

Traffic Cars Speed Driving

Bank Customers Balance Withdrawal

Supermarket Customers Shopping List PaymentPower

GenerationGenerators Power Rotation

PowerDistribution

DistributionWires

Voltage Power Supply

Using Reference 1



12/3212

SYSTEM STUDIES: 1/3

Systems

Saad Haj Bakry

Method ofStudy

Experiment with the

actual system

Experiment with a

model of the

actual system

Use The system exists

Can be operated underdifferent conditions

The system does notexist: planning / design

Working with the actualsystem is not feasible.

Advantages Desirable: No studyvalidation is needed

Flexibility & LowerCost: especiallywith Computers

ProblemsRarely feasible:

costly / disruptiveValidity problem




13/3213

Systems

Saad Haj Bakry

Reference 3

System Analysis:ISO

Operations Research/ Analysis: IBM / ISO

A systematic

investigation of a realor planned system to

determine the

information

requirements andprocesses of the systemand how these relate to

each other and to any

other systems.

The application of

scientific methods tothe solution ofcomplex

problems concerning theoptional allocation ofavailable resources.

Reference 5


SYSTEM STUDIES: 2/3


14/3214

Systems

Saad Haj Bakry

Reference 6

Systems Engineering

Definition The Two Parts

The designof complexinterconnectionof

many elements(asystem)to maximize anagreed upon measure of

system performance.

Modeling in which eachelement of the system andthe criterion for measuringperformance is described.

Optimization in whichadjustable elements are setat values that give the best

possible performance.


SYSTEM STUDIES: 3/3


15/3215

DEFINITIONS

Models

Models: IEEE Definitions

An approximation,representation, or

idealization ofselected aspects of the

structure, behavior,

operation, or othercharacteristics of areal-world process,concept or system

A mathematical orphysical

representation

of thesystem relationships

Saad Haj Bakry

Reference 4 Reference 7



16/3216

TYPES OF MODELS

Models

Saad Haj Bakry

Static MODELS Dynamic

PhysicalModels

Mathematical Models

AnalyticalMethods

Numerical Methods

Algorithms /Heuristics

Simulation




17/3217

STATIC V. DYNAMIC

Models

Saad Haj Bakry

Static Models Dynamic Models

System representation at

a particular time

Time plays no role:

time independent

System is

in balance

System representationconsiders

changes over time

System is

not in balance




18/3218

PHYSICALV. MATHEMATICAL

Models

Saad Haj Bakry

Physical Models Mathematical Models

System representation by

physical means

Electrical,mechanical,

hydraulic or otherphysical representation of

the system

Attributes of systementities are represented byvariables, and activities

are represented by

functions.

A simple model: moving car

distance = speed . time




19/3219

ANALYTICALV. NUMERICAL

Models

Saad Haj Bakry

Analytical Methods Numerical Methods

Investigating / solving

models: using thedeductive reasoning ofmathematical theory

e.g.: Simple models /Models represented by

differential equations

Investigating models /solving equations: using

computationalprocedures

Developing / using

numerical tablescomputed using

numerical methods




20/3220

ALGORITHMS &HEURISTICS

Models

Saad Haj Bakry

Algorithm Heuristic

A finite ordered setof well defined rulesfor the solution of a

problem

To order is to placeitems in an

arrangement inaccordance of

specified rules.

An exploratory method of

solving problems(sophisticated) in which an

evaluation is made of the progress

towards an acceptable finalresult using a series of

approximation results, forexample by a process guided bytrial and error.

For (near) Optimal Solutions:e.g. genetic algorithms /

neural networks

Reference 5


Reference 5


21/32

21Saad Haj Bakry

A numericalcomputationtechnique

used withmathematical

models

Usingcomputers

to imitate

the operationsof various

real worldsystems

Reference 2


SIMULATION: 1/2

Simulation

Reference1


22/32

22

SIMULATION: 2/2

Simulation

Saad Haj Bakry

IEEE ISO

A modelthat behavesor operatelike a given

systemwhen provided bya set of controlled input.

Simulation = EmulationA modelthat accepts thesame inputand produces

the same outputas agiven system

The use of a dataprocessing system

to represent selected

behavioralcharacteristicsof a physical or

abstract system.

Reference 5Reference 4



23/32

23

DISCRETE EVENT SIMULATION

Simulation

Saad Haj Bakry


Reference 2

Use For discrete systems

Characteristics

The state variables change

instantaneouslyatseparate points in time

driven by events..

EventAn instantaneous occurrencethat

may change the state of the system.

ProblemSimple systemscan bemanipulated by hand

calculations. Real time systemsaretoo complicatedfor this manupulations.

Simulation Use digital computers


24/32

24

MONTE CARLO SIMULATION

Simulation

Saad Haj Bakry


Definition Use.

Any simulation studyusing random numbers:

General definition, but of limiteduse

Simulation studies thatuse uniform randomnumbers[U(0,1)]:

Restrictive definition, but ofwider use.

Started inWorld War 2

For the restrictivedefinition:

Generally staticsimulation:passage

of time plays nosubstantive role.

Reference 2


25/32

25

CONTINUOUS SIMULATION

Simulation

Saad Haj Bakry


Reference 2

Use For continuous systems

CharacteristicsThe state variables change

continuouslywith timeMathematical

Representation

Differential equationsgive therelationships for the

rate of change

ProblemOnly simple differential equationscan be solved (finding the values of

the state variables) analytically

Simulation

Using numerical analysistechniques to integrate the

equations, and give values for thechange of the state variables


26/32

26

DISCRETE / CONTINUOUS SIMULATION

Simulation

Saad Haj Bakry


Reference 2

Discrete EventContinuous

State VariableMay cause a discrete

changein the value of acontinuous state

variable.

May cause a

discrete eventtooccur

or to bescheduledat a certain

threshold value.

May cause therelationship governing acontinuous state

variableto change at aparticular time


27/32

27

STEPS OF A SIMULATION STUDY

Simulation

Saad Haj Bakry


Objectives &

Problem

Formulation

Model

Definition

Programming

Model

Validatio

n

Design

ExperimentProduction

Runs

Yes

No

Pilot

RunsProgrammed

Model Valid

Analysis of

ResultsResults

Results should be documented, presented and used

Yes

No

Appropriate level of detail.


28/32

28

ADVANTAGES / DISADVANTAGES

Simulation

Saad Haj Bakry


Reference 2

Use for: Problems:Investigation / alternative design

ofreal world systems

, with

stochastic elements

Performance evaluations ofsystems (existing being planned /

designed) underdifferentconditions / experiments.

Studying systems overa longtime scale (time compression)

Checking the validity ofassumptions foranalytical

models.

One or more simulation

runs are needed foreach set of conditions.

Simulation isexpensive and time

consuming

Valid analyticalmodels are preferred

over simulation.


29/32

29

USE OF SIMULATION: 1/2

Simulation

Saad Haj Bakry

Management & ServicesReengineering of

business processesDesign of service

organizations: e.g. fastfood restaurants,

hospitals, call centers,post offices.

Determining orderingpolicies for inventory

systems.

Designing and operating

transportation systems:e.g. airports, freeways,

ports, subways.

Analyzing financial or

economic systems.

Evaluating logisticrequirements: e.g. in

military systems.


Reference 2


30/32

30

USE OF SIMULATION: 2/2

Simulation

Saad Haj Bakry

Design Evaluations & Manufacturing

Determiningrequirements (HW/ SW)

for:

Information networks

(protocols); andComputer systems.

Evaluating militaryweapons systems.

Designing andanalyzing

manufacturing

systems.

Other applications


Reference 2


31/32

31

SUGGESTED WORK

Saad Haj Bakry


Issue Requirements

Systems Define real life systems,with examples.How to study systems

Models

Define models /

investigations / examples.

SimulationDefine and analyze

simulation


32/32

REFERENCES

Saad Haj Bakry

Seq. Authors / References Title Publication

1 Geoffrey Gordon System Simulation Prentice-Hall, 1978

2Averill M. Law

W. David Kelton

Simulation Modeling andAnalysis McGraw-Hill, 2000

3IBM / ISO, DP Vocabulary,

TC97,SC1, AmericanDictionary of IP, others

IBM Data ProcessingGlossary

IBM, 1977

4 IEEE Standard 610 Computer Dictionary IEEE, 1991

5

ISO / IEC 2382: Information

Technology Vocabulary

Dictionary of Computer

Science: The StandardizedVocabulary ISO/AFNOR 1997

6 S.P. Parker (Editor Encyclopedia of Science &

TechnologyMcGraw Hill, 1984

7 ANSI / IEEE Std 100-1984IEEE Standard Dictionary ofElectrical and Electronics

TermsIEEE, 1984


basic definitions of systems

Documents