1302-traffic modeling techniques

8/13/2019 1302-Traffic Modeling Techniques

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Traffic Modeling Techniques Network Analysis and Planning

Session 1302

CONFIDENTIAL RESTRICTED ACCESS: This information may not be disclosed, copied, or transmitted in anyformat without the prior written consent of OPNET Technologies, Inc.

2007 OPNET Technologies, Inc.


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CONFIDENTIAL RESTRICTED ACCESS: This information may not be disclosed, copied, or transmitted in any format without the prior written consent of OPNET Technologies, Inc. 2007 OPNET Technologies, Inc. 2

1302 Traffic Modeling Techniques

Outline

Motivation for traffic modelingTraffic representationTraffic generation: sources and import methodsTraffic modeling: comparison of various approachesLab #1

Comparing accuracy and speed of explicit and hybrid simulationLab #2

New application deployment study

Lab #3Capacity planning


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Motivation

It is critical to provide good inputsnetwork topology

traffic

It is equally critical to choose a traffic modeling techniquesimulation speed vs. accuracy

This session focuses on modeling traffic

Garbage in

Garbage out


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Outline






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Traffic Samples

WAN link OC48 (30 minute average )

http://loadrunner.uits.iu.edu/weathermaps/abilene/mrtg-data/HSTNng-ATLAng

Application trace


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Real-World Traffic Representation

Types of trafficWAN, LAN, application traffic

Traffic representation in OPNET

Choice of representation depends on modeling purposePacket by packet

End-to-end delays, protocol details, segmentation effectsAggregated traffic

Capacity planning, steady-state routing analysis

Traffic Flows, Device/Link Loads(Background Traffic)

Aggregated Traffic

Explicit TrafficPacket by Packet

OPNET RepresentationTraffic Type


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Parameters in Traffic Representation

Traffic ParametersPacket inter-arrival time or arrival rate

seconds, packets/secondPacket size

bits, bytes etc. bits/sec = bits/pkt * pkts/sec

Variability settingsProbability Distribution Function (PDF)

standard (exponential, bernoulli etc)custom

build your own with PDF editor scripted

Interarrivaltime

File Size


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Outline






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Sources of Explicit Traffic

Explicit traffic injected atApplication Layer

email, HTTP, FTP etcACE, app_demands

Network Layer IP traffic flowsRPG (self-similar traffic generator)

Lower layers Native protocol sources

Ethernet, ATM, Frame Relay etcATM traffic flows


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Sources of Aggregated Traffic

Traffic flows injected atApplication Layer

app_demands Network Layer

IP traffic flowsLower Layers

ATM traffic flowsATM PVC loads

Element loadsCPU utilizationLink loadsDo not require source modelsLoads to flows conversion utility

IP Traffic Flow

app_demand


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Traffic Data Import

TrafficData

Network monitoringsoftware samples traffic

periodically using probesExport to textfiles or OPNETrecognizableformats

Import into OPNET


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Importing Explicit Traffic Packet Trace

Packet tracescaptured usingnetwork analyzer

Sniffer analyzer tcpdumpwindump

ApplicationCharacterizationEditor (ACE)


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Importing Traffic Flow Data

Flow-specific data Demand objects


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Importing Aggregated Traffic Link Loads

Link load information fromCA eHealth

MRTGInfoVistaHP OpenViewSpreadsheet (text info)

Can be converted into trafficflows


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Traffic Flow Creation Wizards

Traffic / Create Traffic FlowsIP UnicastIP MulticastVoIPMPLS VPN


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Scaling Existing Traffic

Global attributesTraffic Scaling Factor

Traffic Scaling ModeAll trafficBackground traffic

Individual demands


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Trending from historical dataRegression algorithms based on least square fitting

Linear, Exponential, Logarithmic, Auto selectSimple growth (linear)Compound growth (geometric)

Traffic Trending

timeAug 2004Feb 2004 Dec 2004

Historical data

Growth

profile(bps)


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Modeling Traffic Priority

Type of Service attribute

DSCPEFAF xy

IP Precedence0,1,,7


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Socket Information

Attribute on IP traffic flowsSource address

Destination addressSource PortDestination PortProtocol

Security and routing analysis


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Traffic Center


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Outline






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Simulation Techniques

Discrete event simulation (DES)Model all traffic (data, signaling, management) using packets

Account for all timers in every protocol layer Perform every state/event transitions of all protocol layers

Analytical simulation (Flow Analysis)Abstract queue performance using mathematical equationsModel traffic as state information in various network elements

Hybrid simulationMix of modeling approaches (discrete event + analytical)Mixture of traffic types (explicit traffic + aggregated traffic)


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Comparison of Various Simulation Techniques


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Micro-Simulation Delay Estimation

Delay estimator ( t) for explicit packets due to additional aggregatedtraffic contending for a common resource (such as a link)

Retrospective micro-sim as lazy evaluation on real packet arrivalSensitive to queuing schemes like PQ, CQ, and WFQ

r1 r2

t

b1 b2 b3

Time

Micro-simulation


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Hybrid Simulation


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Outline

Motivation for traffic modelingTraffic representationTraffic generation: sources and import methodsTraffic modeling: comparison of various approaches

Lab #1



Lab #3

Capacity planning


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Lab 1: Overview

Use different traffic modeling approachesConfigure traffic using IP Traffic Flows

Change the traffic mix to useExplicit trafficBackground trafficHybrid traffic

Compare results and simulation speed

Refer to lab manual for instructions


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Source nodes (videoservers) with different

ToS (1,2,3) Interface with WFQ

100 video users (MPEG4) - 3 available service classes

Queuing delays?

Destination nodes

Lab 1: Network Model


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B R E A K


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Effects on Background Traffic Flows

Quality of Service (QoS)MarkingClassificationQueuing

Load Balancing:

Split traffic flows proportionally among available paths

OverheadsTraffic volumes and packet sizes adjusted to account for protocol overheads

Segmentation (DES only)Reduce packet size to within MTU


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Load Balancing Background Traffic Flows

0.75

0.25

0.5 * 0.75 = 0.375

0.375

0.25

0.25

0.3750.375

1302 ffi d li h i


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Modeling Efficiency

Tradeoff: speed vs. accuracyMore details = less speed

Discrete Event Simulation (DES) vs. Flow AnalysisUse Flow Analysis where applicable

Routing, capacity planningSimplify DES model

Reduce network scopeAggregate traffic

Simulation speedup in DESHybrid simulation

Traffic mix attributeTarget traffic + baseline traffic



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Hybrid Simulation: Traffic Mix Attribute

Attribute on IP/ATM traffic flowsConfiguring traffic type mix

ExplicitBackgroundMixed (hybrid) use small percentage of explicit (not values like 50%)



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Hybrid Simulation: Target Traffic Approach

Target trafficModel all details using explicit mode

Baseline trafficModel as aggregated traffic



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g q

Typical Workflow

Application deployment studyImport network topology

Deploy one instance of new application from packet traceModel as explicit traffic

Import baseline network loadModel as link loads

Deploy multiple users of new applicationModel as traffic flows

ACE to flows conversion utility



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Outline

Motivation for traffic modelingTraffic representation

Traffic generation: sources and import methodsTraffic modeling: comparison of various approachesLab #1

Compare accuracy and speed of explicit and hybrid simulation

Lab #2 New application deployment study

Lab #3

Capacity planning



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Lab 2: New Application Deployment

Import application trace file and convert it into OPNET trafficDeploy application on top of existing baseline traffic

Study the application end-to-end performanceSimulate impact of many application users using traffic flows



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Lab 2: Application Trace and Network Model



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Flow Analysis Concepts

Traffic Data1) Traffic flows2) Device/link load

Topology Data

Flow analysis engine1) Fast2) Steady-state analysis3) Aggregated traffic only

Discrete Event Simulation1) High-fidelity1) Transient and steady-state analysis2) Packet-by-packet traffic



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RoutingCapacity planning

SurvivabilityQuality of Service (QoS)Delay analysisVoIP deployment

Flow Analysis Capabilities



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Outline

Motivation for traffic modelingTraffic representation

Traffic generation: sources and import methodsTraffic modeling: comparison of various approachesLab #1

Comparing accuracy and speed of explicit and hybrid simulation

Lab #2 New application deployment study

Lab #3

Capacity planning



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Lab 3: Capacity Planning

Corporate WAN upgradeIdentifying bottlenecksApply QoS to improve voice traffic performanceUpgrade links to solve existing utilization problems.Forecast traffic growth and identify future bottlenecks.

Refer to lab manual for instructions



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Session 1619 Importing Network Traffic with XDI (formerly MVI)

Session 1505 Building Traffic Source ModelsSession 1554 Case Studies: Specialized Topics in Traffic and QoSModelingSession 1350 Network Traffic Characterization and CapacityPlanningSession 1813 from 2006 Traffic Behavior and Queuing in a QoSenvironment

Presents queuing modeling in a QoS environment (by Prof. Bertsekas)

Other Sessions : Traffic Modeling



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Take-Away Points



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Reference Slides

Following slides are for reference



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Analytical Coupled with Micro-Simulation

r1r2

t + a

b1 b2 b3

Time

Micro-simulationAnalytical-simulation

a

When real packets are separated by a long intervalLazy evaluation in two stages: analytical + micro-simulation

Currently implemented for FIFO queues onlyGain in simulation speed compared to pure micro-simulation


A t d T ffi J t N b t


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Aggregated Traffic Just a Number toCompute a Delay

Aggregated traffic in OPNETTraffic flows (routed background traffic)Device/link loads (static background traffic)

Common to both type of aggregated trafficInternal representation: just a number for a given node/link Effects: only one effect to produce a delay

One difference between the two types of aggregated trafficTraffic flows (routed background traffic) needs to be propagated to eachnode in the flow path tracer packets (propagators)

2Mbps2Mbps

2Mbps

2Mbps2Mbps

2Mbps

2Mbps2Mbps

2Mbps

2Mbps

2Mbps2Mbps



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Defining Traffic Flows

3 basic steps



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Defining Traffic Flows (cont.)

Each flow is broken down into intervals as specified

Interval : 300-600 seconds



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I1 I2 I3 I4 I5

Simulating Background Traffic Flows

Refresher tracer packets

I1

P1 P3 P4 P5P2


Simulating Background Traffic Flows


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Simulating Background Traffic Flows(cont.)

Sending new information on traffic level changes

start time = 150.00.0 I1 I2 I3 I4 I5

1302-traffic modeling techniques

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