network management and traffic analysis for wimax

Network Management and Traffic Analysis for Wireless MAN 1

NETWORK MANAGEMENT AND TRAFFIC ANALYSIS FOR WIMAXSpeaker: Dedi Rahmawan Putra (95598052)Supervisor: Dr. Kai-Wei Ke

July, 28 2008

Network Management and Traffic Analysis for Wireless MAN

2

Outline

July, 28 2008

Simple Network Management Protocol Development of Network Management

Station (NMS) Network Management Deployment on

IEEE 802.16 system Traffic Analysis Closing Remarks


SNMPSIMPLE NETWORK MANAGEMENT PROTOCOL

Principle OperationStandardsObject Addressing

July, 28 2008

4

July, 28 2008Network Management and Traffic Analysis for Wireless MAN

SMI (Structure of Management Information)Define how management information may look

like SMIv2 (currently used)

MIBs (Management Information Bases)Tell what management information exists MIB-II (currently used)

SNMP (Simple Network Management Protocol)Define how information is exchanged SNMPv1, SNMPv2c, SNMPv3

Standards

5


NMS

Agent

MIB

poll

pollpoll

TRAPS

GET/SET

variable

table

MIBMIBAgent

Agent

Principle Operation

6


Ensuring that each variable

gets a unique name

for interne

t people

for company

or university

Object Addressing (1)

OID: 1.3.6.1.2.1

7


OID: 1.3.6.1.2.1 wmanIfMib is defined under

this branch

Object Addressing (2)

OID: 1.3.6.1.2.1.1.1

e.g.Scalar Instance: 1.3.6.1.2.1.1.1.0Table Instance: 1.3.6.1.2.1.2.1.1.1

GET 1.3.6.1.2.1.1.1.0 = “MP.16 BS v.130” Column number

Index Value


THE DEVELOPMENT OF NETWORK MANAGEMENT STATION (NMS)ChallengesSystem Context DiagramSystem ArchitectureFront PageSimple NMS WorkflowNMS DEMONSTRATION

July, 28 2008


9

July, 28 2008

Remote Accessibility Continuous Monitoring Cross Platform Widely Applicable for SNMP-Capable Device User friendly tools and menu Configurable Objects parameters Satisfying Requirements: Operation, Administration,

Maintenance, Provisioning, Functions Robust Feature Extendable

Challenges

10


MIB

MIB

MIB

User

Presentation Logic

Control Logic

Database Driver

SNMP Tools

LAN/MAN/WAN

Network Management

Station

Database Server

Agents

WiMAX BS

WiMAX SS Access Point Printer

SNMP

SNMP

SNMP

SNMP SNMPPC

MIBMIB

System Context Diagram

11


Database

Session Beans

Entity Beans

ServletsJSP Pages

Java EE Server

Web Container

EJB Container

Client

Browser

Applets

Class Library

System Architecture

12


Front Page

13


Object Registra

tionAgent

Registration

Agent-Object

MappingObject

Monitoring

Simple NMS Workflow


NMS DEMONSTRATION

July, 28 2008


NETWORK MANAGEMENT DEPLOYMENT ON IEEE 802.16 SYSTEM

Network Management System DeploymentChallengesMonitoring ParametersMonitoring ScenarioMonitoring Result Snapshots

July, 28 2008

16


WiMAX BS140.124.183.210

WiMAX SS-1140.124.183.211

AP-1140.124.183.213

Internet

WiMAX SS-2140.124.183.212

AP-2140.124.183.214

NMS140.124.183.224

User Client

Clients

Clients

Gateway

Wired or Wireless

Network Management System Deployment

17


Wireless Environment Unstable WiMAX Test-Bed Network

System Limited MIB Agents Time Constrain Collecting Adequate Data

Challenges

18

Monitoring Parameters


QoS Service Class: UGS, rtPS, nrtPS, Best Effort Modulation Type: BPSK, QPSK, 16QAM, 64QAM Traffic Intensity: light load, heavy load Data flow: Downlink (DL), Uplink (UL) Data Traffic:

UGS: VoIP rtPS: MPEG video, web-TV nrtPS: file transfer (FTP) BE: internet application(web browsing), email


19

Monitoring Scenario

July, 28 2008

WiMAX BS140.124.183.210

WiMAX SS-1140.124.183.211

WiMAX SS-2140.124.183.212

WiMAX Wireless Mediumeth0 eth0

eth0

OUTIN OUT

IN

OUT

IN

wmanIfBsSsPacketCounterTableNOT

EXIST

ifTable on MIB-II StandardifInOctets

ifInUcastPktsifOutOctetsifOutUcastPkts

• May introduce inaccurate result• Traffic Pattern can be observed


20

Monitoring Result Snapshots

July, 28 2008

e.g. Best Effort Heavy Load on SS-1


TRAFFIC ANALYSISSelf-Similar vs Poisson Traffic ModelChallengesUGS Service ClassrtPS Service ClassnrtPS Service ClassBest Effort Service ClassAnalysis Summary

July, 28 2008

22


Poisson Model Self-Similar ModelConsiders network arrival as a random process.

Uses autocorrelation and does not consider the network traffic to be random.

Does not scale the bursty traffic properly.

Scales bursty traffic well, because it has similar characteristics on any scale.

In fine scale, bursty traffic appears bursty, while in coarse scale, bursty traffic appears smoothed out and looks like random noise.

Gives more accurate pictures due to Long Range Dependence in the network traffic.

Self-Similarity vs. Poisson Model

23


Inaccurate Data source Short Duration Data Self-similarity assessment methods:

Pictorial Guess, Variance-Time Plot, Rescaled Adjusted Range (R/S) Plot

Hurst Parameter Estimation

Challenges


24

UGS Service Class (1)

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0 100 200 300 400 5000

50

100

150ifOutUcastPkts-SS1 (UGS Heavy)

Time Unit = 1000 milliseconds

Valu

e

0 10 20 30 40 500

5000



Valu

e

0 50 100 150 200 2500

1000



Valu

e

0 100 200 300 400 5000

20

40

60ifOutUcastPkts-SS1 (UGS Light)


Valu

e

0 10 20 30 40 50 600

1000

2000



Valu

e

0 50 100 150 200 250 3000

200

400



Valu

e


25

0 0.5 1 1.5 2 2.5 30

1

2

3R/S Plot ifOutUcastPkts-SS1 (UGS-Heavy)

log10(N)

log1

0(R/

S)

0 0.5 1 1.5 2 2.5 3-2

-1

0

1

2Variance Time Plot ifOutUcastPkts-SS1 (UGS Heavy)

log10(m)

log1

0(Va

rianc

es)

UGS Service Class (2)

July, 28 2008

0 0.5 1 1.5 2 2.5 3-2

-1

0

1Variance Time Plot ifOutUcastPkts-SS1 (UGS Light)

log10(m)

log1

0(Va

rianc

es)

0 0.5 1 1.5 2 2.5 30

1

2

3R/S Plot ifOutUcastPkts-SS1 (UGS Light)

log10(N)

log1

0(r/s

)

β = -1.0329

H = 0.4836

Slope = -1 Slope = -1β = -0.8488

H = 0.5756

Slope = 0.5

Slope = 1Slope = 0.5

Slope = 1H = 0.6828 H = 0.5316


26

rtPS Service Class (1)

July, 28 2008

0 100 200 300 400 5000

100

200

300ifOutUcastPkts-SS1 (rtPS Heavy)


Valu

e

0 10 20 30 400

5000

10000



Valu

e

0 50 100 150 2000

1000

2000



Valu

e

0 100 200 300 400 5000

100

200

300ifOutUcastPkts-SS1 (rtPS Light)


Valu

e

0 50 100 150 2000

1000



Valu

e

0 5 10 15 20 25 30 350

2000

4000



Valu

e


27

0 0.5 1 1.5 2 2.5 30

1

2

3

4Variance Time Plot ifOutUcastPkts-SS1 (rtPS Heavy)

log10(m)

log1

0(Va

rianc

es)

rtPS Service Class (2)

July, 28 2008

0 0.5 1 1.5 2 2.5 30

1

2

3Variance Time Plot ifOutUcastPkts-SS1 (rtPS Light)

log10(m)

log1

0(Va

rianc

es)

0 0.5 1 1.5 2 2.5 30

0.5

1

1.5

2

2.5

3R/S Plot ifOutUcastPkts-SS1 (rtPS Heavy)

log10(N)

log1

0(r/s

)

0 0.5 1 1.5 2 2.5 30

1

2

3R/S Plot ifOutUcastPkts-SS1 (rtPS Light)

log10(N)

log1

0(r/s

)

β = -0.4495H = 0.7752

Slope = -1Slope = -1

β = -1.1594H = 0.4203

Slope = 0.5

Slope = 1

Slope = 0.5

Slope = 1H = 0.5507 H = 0.7686


28

nrtPS Service Class

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0 100 200 300 400 5000

200

400

600ifOutUcastPkts-SS1 (nrtPS Heavy)


Valu

e

0 50 100 150 200 2500

2000

4000



Valu

e

0 10 20 30 40 500

1

2

3x 10



Valu

e

0 100 200 300 400 5000

200

400

600ifOutUcastPkts-SS1 (nrtPS Light)


Valu

e

0 10 20 30 400

1

2x 10



Valu

e

0 50 100 150 2000

2000



Valu

e


29

nrtPS Service Class

July, 28 2008

0 0.5 1 1.5 2 2.5 31

1.5

2

2.5

3

3.5

4Variance Time Plot ifOutUcastPkts-SS1 (nrtPS Heavy)

log10(m)

log1

0(Va

rianc

es)

0 0.5 1 1.5 2 2.5 31

1.5

2

2.5

3

3.5

4Variance Time Plot ifOutUcastPkts-SS1 (nrtPS Light)

log10(m)

log1

0(Va

rianc

es)

0 0.5 1 1.5 2 2.5 30

0.5

1

1.5

2

2.5

3R/S Plot ifOutUcastPkts-SS1 (nrtPS Heavy)

log10(N)

log1

0(r/s

)

0 0.5 1 1.5 2 2.5 30

0.5

1

1.5

2

2.5

3R/S Plot ifOutUcastPkts-SS1 (nrtPS Light)

log10(N)

log1

0(r/s

)

β = -0.2832 H = 0.8584

Slope = -1 Slope = -1

β = -0.5039

H = 0.7480

Slope = 0.5

Slope = 1

Slope = 0.5

Slope = 1

H = 0.8409 H = 0.5933


30

Best Effort Service Class (1)

July, 28 2008

0 100 200 300 400 5000

100

200

300ifOutUcastPkts-SS1 (BE Heavy)


Valu

e

0 20 40 60 800

5000



Valu

e

0 100 200 300 4000

1000

2000



Valu

e

0 100 200 300 400 5000

200

400ifOutUcastPkts-SS1 (BE Light)


Valu

e

0 10 20 30 40 500

5000



Valu

e

0 50 100 150 200 2500

1000

2000



Valu

e


31

Best Effort Service Class (2)

July, 28 2008

0 0.5 1 1.5 2 2.5 30.5

1

1.5

2

2.5

3

3.5Variance Time Plot ifOutUcastPkts-SS1 (BE Heavy)

log10(m)

log1

0(Va

rianc

es)

0 0.5 1 1.5 2 2.5 31

2

3

4Variance Time Plot ifOutUcastPkts-SS1 (BE Light)

log10(m)

log1

0(Va

rianc

es)

0 0.5 1 1.5 2 2.5 30

0.5

1

1.5

2

2.5

3R/S Plot ifOutUcastPkts-SS1 (BE Heavy)

log10(N)

log1

0(r/s

)

0 0.5 1 1.5 2 2.5 30

0.5

1

1.5

2

2.5

3R/S Plot ifOutUcastPkts-SS1 (BE Light)

log10(N)

log1

0(r/s

)

β = -0.5333

H = 0.7333Slope = -1

Slope = -1

β = -1.1141

H = 0.4429

Slope = 0.5

Slope = 1Slope = 0.5

Slope = 1

H = 0.7958 H = 0.7413


32

Analysis Summary

July, 28 2008

Rank

QoS Category

Traffic Intensi

tyPictorial Guess

Hurst variance

plot

Hurst by R/S Plot

Average Hurst

1 nrtPS Heavy Self-Similar 0.8584 0.8409 0.8497

2 Best Effort Heavy Self-

Similar 0.7333 0.7958 0.7646

3 nrtPS Light Self-Similar 0.7480 0.5933 0.6707

4 rtPS Heavy Poisson 0.7752 0.5507 0.66305 rtPS Light Poisson 0.4203 0.7686 0.59456 Best

Effort Light Self-Similar 0.4429 0.7413 0.5921

7 UGS Heavy Uniform 0.4836 0.6828 0.58328 UGS Light Uniform 0.5756 0.5306 0.5531


CLOSING REMARKS

ConclusionsFuture Works

July, 28 2008

34

Conclusions


The NMS had been designed, implemented, and deployed successfully.

The monitoring procedure was done on Ethernet interface using the objects of MIB-II standard.

The response time in notifying the network manager much depends on wireless link quality and the traffic intensity.

Different QoS class and traffic intensity generated different traffic behavior and self-similarity degree.

35

Future Works


Continuing the incremental sequence to NMS Development. Defining additional features to support more functionality

into NMS system, e.g. providing statistical analysis Integrating the NMS with another system, e.g. developing

Java application client. Developing J2ME application is also possible for operation on

mobile device. Establishing additional research on self-similar model

towards WiMAX QoS. Collecting more rigorous data to get more convincing result. Repeatable analysis and measurement once the WiMAX MIB

interface is available.


THANK YOU

July, 28 2008


37

Network Management Requirement Analysis

July, 28 2008

Operation deals with keeping the network up and running smoothly.

Administration deals with keeping track of resources in the network and how they are assigned.

Maintenance regards with performing repairs, upgrades, and corrective and preventive measures to make the managed network run better.

Provisioning is concerned with configuring resources in the network to support a given service.

Functions that are performed as part of network management accordingly.

38

Retrieving Scalar Value


1.1.0

1.2.1.0 1.2.2.0

Object OID: 1.1

Instance OID: 1.1.0

Value

GET 1.1.0 = 140.124.181.210

39

Retrieving Table Entries Value


X.C.I = OidOfTable.ColumnNumber.IndexValue

new-MIB.routeTable.next.8 = 3

destination

1.3.2.8 = 3

40


FeaturesSatisfied Requirements

Operation Administration Maintenance Provisioning FunctionsObject Registration x xObject Summary xAgent Registration x xAgent Summary xAgent object Management x x xAgent Status Control x x xStatic Monitoring x x xDynamic Monitoring x xGrouped Monitoring x xManager System Control x xAgent Management Structure x xAdmin Login Control x x xServer Time x xPing Tool x x xGet Tool x x xSet Tool x x x xLogs of Activities x x

Feature Refinement

41


+getId() : Long+setId(in id : Long) : void+getIpAddress() : String+setIpAddress(in ipAddress : String) : void+getName() : String+setName(in name : String) : void

-id : Long-ipAddress : String-name : String-type : String-deviceStatus : Boolean-monitorStatus : Boolean-snmpVersion : int-snmpPort : int-communityWrite : String-communityRead : String

AgentEntity

+getId() : Long+setId(in id : Long) : void+getName() : String+setName(in name : String) : void+getSyntax() : String+setSyntax(in syntax : String) : void

-id : Long-oid : String-name : String-syntax : String-maxaccess : String-description : String-retrievalMethod : String-asDefault : Boolean-intervalRetrieval : int-enumeration : Boolean

ObjectEntity

+getId() : Long+setId(in id : Long) : void+equals(in object : Object) : Boolean

-id : LongAgentObjectEntity

+getId() : Long+setId(in id : Long) : void+getInstanceValue() : int+setInstanceValue(in value : int) : void+getMeaning() : String+setMeaning(in meaning : String) : void

-id : Long-instanceValue : int-meaning : String

EnumInstanceEntity

+getId() : Long+setId(in id : Long) : void+getMoment() : Long+setMoment(in moment : Long) : void+getInstanceValue() : String+setInstanceValue(in value : String) : void

-id : Long-moment : Long-retrievalValue : String

MonitoringEntity

-agentEntity

0..*1

0..*

-objectEntity

1

1

-gateway0..1

1

-objectEntity0..*

-agentObjectEntity 0..*

1

Implementation Class Diagram

42


Header

Footer

Content

Content

Menu

Content

Content

Containers and contents are implemented using JSP

GUI Layout

43


aimed to detect the device status utilizes isReachable() function call

provided by Java. Implemented using Stateless Session

Bean within EJB Container.

Ping Function

44

Get Function


Used for monitoring feature and simple Get feature.

Implemented using Stateless Session Bean within EJB container.

To perform the value retrieval from a specific object ID in the MIB agent.

Utilizing Snmp4j library to create SNMP PDU and execute Get command.

45



Used for simple Set tool feature To create SetRequest-PDU and execute Set command, we also utilize Snmp4j library.

Set Function

46


To schedule a sequence of actions by giving a certain delay in between.


Constructed by 3 sub functions: initiating timer, cancelling timer, timeout actions.

Used for dynamic monitoring and Auto-ping feature.

Timer Interval

47

Chart Generator


Generates the chart presentations on monitoring procedure.

Utilizing JFreeChart library. Two kinds of charting presentation available: bar

or histogram time series chart, and line time series chart.

Implemented in: Servlet within web container: for Static PNG image Applet within Applet Class Library: for real monitoring

The chart is a time series domain chart drawn against the retrieval value

48


displaying hidden field

Object Registration UI

49


Object ID Object Name Syntax: the object data type Max-Access: the maximum possible access Description Make Default for New agent: special field

intended to distinguish which objects should be included in a newly-registered agent by default.

Object Registration Field

50


meaningless status value for human readable

more understandable meaning

Syntax Enumeration

51


Once: retrieved once when the monitoring starts. Eg: SystemDescription, systemName.

Continuously-Updated-Value: retrieved and updated regularly. Eg: systemUpTime.

Line-Chart: retrieved regularly, the previously retrieval data will be kept.

Bar-Chart: basically similar with Line-Chart one, but using bar-chart or histogram to illustrate the monitored object.

newly appeared field

Object Retrieval Method

52


hidden by default

show hidden field

Agent Registration UI

53


IP Address Agent name Device type: the level position in the WiMAX network

deployment hierarchy: WiMAX-BS, WiMAX-SS, AP, CLIENT

Upper level gateway: which upper gateway the device belongs to.

SNMP version : which compatible SNMP standard the device agent is designed for: v1, v2c, v3

Read Community: community string for read access. Write Community: community string for write access. SNMP Port

Agent Registration Field

54


Need confirmation: monitoring in progress? restart

Object naming convention: name + index for Table instances

Agent Object Management

55


•OK•Need Attention•Not Performed

Agent Status Control

56


Used for: Once and Continuously-Updated-Value

Static Monitoring

57


Line-Chart

Object NameBar-Chart(Histogram)

Dynamic Monitoring

58


wmanIfMib = 1.3.6.1.2.1.10.184

wmanIfMibObjects = 1.3.6.1.2.1.10.184.1

wmanIfBsObjects (1) wmanIfSsObjects (2) wmanIfCommonObjects (3)

wmanIfBsPacketCswmanIfBsCpswmanIfBsPkmObjectswmanIfBsNotificationwmanIfBsPhy

wmanIfSsPkmObjectswmanIfSsNotificationwmanIfSsPhy

wmanIfCmnPacketCswmanIfCmnCpswmanIfCmnPkmObjects

wmanIfMibConformance = 1.3.6.1.2.1.10.184.2

wmanIfMibGroups (1) wmanIfMibCompliances (2)

IEEE Std. 802.16f-2005

59


Object ID Object Name Syntax Max-Access

1.3.6.1.2.1.2.2.1.2.x1 ifDescr OCTET-STRING READ-ONLY1.3.6.1.2.1.2.2.1.5.x1 ifSpeed Gauge32 READ-ONLY1.3.6.1.2.1.2.2.1.10.x1 ifInOctets Counter32 READ-ONLY1.3.6.1.2.1.2.2.1.11.x1 ifInUcastPkts Counter32 READ-ONLY1.3.6.1.2.1.2.2.1.12.x1 ifInNUcastPkts Counter32 READ-ONLY1.3.6.1.2.1.2.2.1.14.x1 ifInErrors Counter32 READ-ONLY1.3.6.1.2.1.2.2.1.16.x1 ifOutOctets Counter32 READ-ONLY1.3.6.1.2.1.2.2.1.17.x1 ifOutUcastPkts Counter32 READ-ONLY1.3.6.1.2.1.2.2.1.18.x1

ifOutNUcastOctets Counter32 READ-ONLY

MIB Extraction

60


Management Scenario Flowchart


61

WiMAX QoS Classes

July, 28 2008

UGS (Unsolicited Grant Service) Used for real-time constant bit rate service that gives periodic transfer data at similar packet size (burst) and sensitive towards throughput, latency, and jitter.

Real Time Polling Service (rtPS)Used for real-time service flows with periodic variable size data packets which is sensitive toward the throughput and latency, but with loosely tolerance compared to UGS guaranteed rate and delay requirement

Non-Real-Time Polling Service (nrtPS) Used for non real-time services with regular variable size burst that needs intensive throughput with minimal guarantee on its latency

Best Effort (BE) This service is dedicated to the network traffic that doesn’t require guaranteed data rate and delay


62

Equations

July, 28 2008

Variance-Time

Rescaled Adjusted Range (R/S)

Linear Regression

network management and traffic analysis for wimax

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