traffic engineering in large ip networks with mpls

8/6/2019 Traffic Engineering in Large Ip Networks With Mpls

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Traffic Engineering inTraffic Engineering inLarge IP NetworksLarge IP Networks

with MPLSwith MPLSKey issues for successful

implementations

David Drury

V.P Technology Strategy


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MPLS a keytechnology in

building a profitable

New Public network


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Transmission

Traffic

Engineering

ServiceIP IP IP IP

SONET/SDH

ATM ATM

The Internet today (1995-)The Internet today (1995-)

Three Layer Architecture

DWDM


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TopicsTopics

Traffic Engineering in a Best Efforts IPnetworkTraffic Engineering in a Multi-service IP

networkThe design of a Label Switched Router


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BenefitsBenefits

Traffic engineering places the traffic wherethe network is, maximizing revenue from agiven capacity networkIt enables the support of premium servicesPremium services generate the most

profitability.MPLS is a key technology in building a

profitable New Public Network


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Traffic Engineering in BestTraffic Engineering in BestEffort IP NetworksEffort IP Networks


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Current IGPs lead to Hyper-AggregationCurrent IGPs lead to Hyper-Aggregation

S

D

TRAFFIC FOR D

SHORTEST PATH ROUTED

CONGESTION

MASSIVE

CONGESTION


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Current IGPs lead to Hyper-AggregationCurrent IGPs lead to Hyper-Aggregation

S

D

TRAFFIC FOR D

SHORTEST PATH ROUTED

9 UNDER ULTILIZED]

4 OVERUTILIZED ]

CONGESTION

MASSIVE

CONGESTION

LINKS


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Answer = Traffic EngineeringAnswer = Traffic Engineering

Objectives Map actual traffic efficiently to available

resources

Controlled use of resources Redistribute traffic rapidly and effectively in

response to changes in network topology -particularly as a consequence of line orequipment failure

Note this complements Network Engineering Putting the network where the traffic is


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Network resource characteristicsNetwork resource characteristics

Off-line

provisioning

Constraint

Based Routing

NMS gathers

network statistics

Optimal flow mesh

calculated offline

End-to-end path

explicitly

provisioned

QoS aware routing

distributes load

information

New flows routed

along best available

path

Endpoints

provisioned with

constraints

Network load

information

Best effort path

selection

Service

provisioning

NOTE: Both methods rely on a connection-oriented transmissioninfrastructure


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Explicit Routing MethodsExplicit Routing Methods

SONET Trail

ATM PVCs

ATM DirectedSPVCs

MPLS ExplicitRouted LSPs

OpticalWavelengths

Method Granularity Protection Topology Jitter

Gbps

Mbps

Kbps

Kbps

Kbps

Yes(ms -s)

Yes(ms- mins)

No

Yes(ms - s)

Yes(ms - s)

Linear*

* Some vendors provide ring-based DWDM implementations (e.g. Marconi Communications)

Linear/Ring

Any

Any

Any

Lowest

Lowest

Low

Low

Medium


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Constraint Based RoutingConstraint Based RoutingMethodsMethods

ATM

MPLS

Optical

MethodStandard

BodyRouting Signalling Available

OIF?

ATMForum

IETF

OSRP,WaRP..

PNNI

OSPF(TE)

orIS-IS(TE)

PNNI

RSVP -TE

orCR- LDP

Future?

Now

Trials

Control planes are independent of each other

OSRP,WaRP..


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Constraint Based RoutingConstraint Based RoutingMethodsMethods

ATM

MPLS

Optical

MethodStandard

BodyRouting Signaling Available

IETF

IETF

IETF

OSPF linePNNI like

PNNI

OSPF orIS-IS*

PNNI

RSVP orLDP

Future

Trials

Trials

PNNIor other?

A single control plane across all layers

MPLS MPLS

MPLS MPLS

MPLS MPLS


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Transmission

Traffic

Engineering

ServiceIP IP IP IP

SONET/SDH

DWDM Photonics

MPLS MPLS

The MPLS-Enabled InternetThe MPLS-Enabled InternetAnd The Product MigrationAnd The Product Migration

Same Three Layer Architecture


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Smart ConnectionsSmart Connections

Implementation techniques beyond the standardprotocols that improve and automate traffic engineering reduce operational costs

Increase resilience

reduce recovery time

Estimated BandwidthBandwidth measurementConnection PrioritiesPacingFall back/Optimization


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400Mbps @ 60%

25Mbps @ 30%

100Mbps @ 50%

400Mbps @ 62.5%

100Mbps @ 60%

25Mbps @ 70%

SELECTED

PATH

Traffic Engineering Using EstimatedTraffic Engineering Using EstimatedBandwidth for Best Effort TrafficBandwidth for Best Effort Traffic

BEFORE25Mbps @ 30% 25Mbps @ 70%

100Mbps @ 50% 100Mbps @ 60%

400Mbps @ 62.5%400Mbps @ 60%

AFTER ADDING 10Mbps

S

D

400Mbps @ 60%

25Mbps @ 30%

100Mbps @ 60%

S

D


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Bandwidth measurementBandwidth measurement

Augment estimated BandwidthMeasure actual usage

link utilization

rate of change of link utilization buffer occupancy

rate of change of buffer occupancy

Compute effective b/w utilizationDistribute effective b/w with IGPUse as another constraint in the path computation

processRESULT = more efficient Traffic distribution


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Resilience - connectionResilience - connectionprioritiespriorities

Active communication of failure to routing andsignaling layerAbility to prioritize connections - the most

important are released first and re-establishedfirst over alternate paths.Fast signaled re-establishment of alternative

path can meet low service restoration times.

On a large network only pre-establishment ofalternative paths can meet


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PacingPacing

Failure may affect 1,000s LSPsPacing groups LSPs into priority order and re-

establishes a group at a timeAllows new resource consumption to be flooded

before the next group is re-establishedMinimizes overall re-establishment time (by

reducing connection failures)Makes new distribution closer to optimum


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Fall back - OptimizationFall back - Optimization

What happens to traffic established over less thanoptimal paths Due to network failure Due to congestion when established

Fallback/Path Optimization continually re-checks for better paths Reverts to that better path Uses make before break to do so in a non-service affecting

manner

Under management control Can affect network stability if not done well

Result - higher overall network efficiency


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Post script - performance implicationsPost script - performance implications

High control plane performance is critical for:- Establishment of data driven LSPs

Performance of advanced path computation algorithms

Minimizing LSP fault recovery times

Cross country re-route times measured at under 200msec

Dynamic Headroom

IGP scaling

Makes the automation of the traffic engineering task

practical


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Traffic Engineering in Multi-Traffic Engineering in Multi-service IP Networksservice IP Networks


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The Convergence DimensionThe Convergence DimensionPredictabilityPredictability

BANDWIDTH

0.1M 1M 10M 100M 1G

1M

10M

100M

1B

PREDICTABILITY


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BANDWIDTH

0.1M 1M 10M 100M 1G

1M

10M

100M

1B

PREDICTABILITY BANDWIDTH LATENCY

JITTER

ERROR RATE

SERVICE INTERUPTION


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BANDWIDTH

0.1M 1M 10M 100M 1G

1M

10M

100M

1B

PREDICTABILITY BANDWIDTH LATENCY

JITTER

ERROR RATE

SERVICE INTERUPTION

WebApplications


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BANDWIDTH

0.1M 1M 10M 100M 1G

1M

10M

100M

1B

PREDICTABILITY

WebApplicationsHigher Priority Web Applications


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BANDWIDTH

0.1M 1M 10M 100M 1G

1M

10M

100M

1B

PREDICTABILITY


CoS

IPPS


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BANDWIDTH

0.1M 1M 10M 100M 1G

1M

10M

100M

1B

PREDICTABILITY


CoS

IPPS

VOICE


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BANDWIDTH

0.1M 1M 10M 100M 1G

1M

10M

100M

1B

PREDICTABILITY


CoS

IPPS

VIDEO

VOICE

ECommerce

ASP


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BANDWIDTH

0.1M 1M 10M 100M 1G

1M

10M

100M

1B

PREDICTABILITY


CoS

IPPS

VIDEO

VOICE

ECommerce

ASP

HardQoSIP

FS


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The key to Premium Services

is Infrastructure Predictability

The key to Premium Services

is Infrastructure Predictability

Critical ConclusionCritical Conclusion

So how do we deliver

Predictability?

So how do we deliver

Predictability?


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Traffic Engineering in a multi-serviceTraffic Engineering in a multi-serviceIP netIP net

Best effort to multi-service is the most importanttransition facing ISPs today

Traffic engineering problem is the same as for a besteffort network BUT

Many more constraints on the path computation e.g. EF - Peak frame rate, average frame rate, max burst size,

loss sensitivity, delay, delay variation etc

e.g. AF - Relative priority


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Pre-computationPre-computation

Scaling the path computation process Define common traffic profiles (sets of constraints) Pre-compute the paths for each profile Cache exception profiles Re-compute on change in network state. Path for a new LSP determined from the profile table . Tie break when more than one path exists (randomization along

equally congested paths) RESULT = Connection time independent of network size


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The design of a Label SwitchedThe design of a Label SwitchedRouterRouter


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Multi-service TE needs data planeMulti-service TE needs data planesupportsupport

Many more requirements on the data plane of the LSR toisolate different traffic classes Policing (metering) and marking

Intelligent buffer management

Per traffic class per port queuing Intelligent congestion management

Three color RIO

Per LSP scheduling and hierarchical shaping (LSPs withinLSPs)

Line rate performance

Order 106 LSPs


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Edge LSREdge LSR

LSRs at the edge of an MPLS domain have additionaldata and control plane requirements

Interfaces between labeled and unlabeled IP packetsAdds or pops labels as appropriateClassifies packets to Forwarding Equivalence Classes

(FEC)Maps Diff-serv to MPLS LSPsForwards unlabeled IP packets


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LSR designLSR design

The design of both the data and control plane of an LSRare critical to effective traffic engineering

As the next sequence shows, much of the requirementsderive from the current generation ATM switches in the

core of the Internet and not the edge routers


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INPUTS

BUFFER

MANAGEMENT

OUTPUT

BUFFER

Switch Control

Processor

Switch Control

Processor

Switch ApplicationsSwitch Applications

OUTPUTS

ATMATM

STM-1/4/16

STM-1/4/16

Smart Connections

Pre-computation

PNNI routing

PNNI signaling

Policing

Marking

Buffer

Allocation

Packet Drop

Per Port

Per Priority

Per Flow

Queuing

Flow

Merging

Hierarchical

Scheduler

Shaper

10-40G

Fabric(s)

Current Internet Core ATM SwitchCurrent Internet Core ATM Switch


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INPUTS

BUFFER

MA

NAGEMENT

OUTPUT

BUFFER

Switch Control

Processor

Switch Control

Processor


OUTPUTS

ATMATM

STM-1/4/16

STM-1/4/16

Smart Connections

Pre-computation

PNNI routing

PNNI signaling

OSPF(TE), IS-IS(TE), BGP4

RSVP-TE, CR-LDP

Policing

Marking

Buffer

Allocation

Packet Drop

Per Port

Per Priority

Per Flow

Queuing

Flow

Merging

Hierarchical

Scheduler

Shaper

10-40G

Fabric(s)

Core Internet MPLS NodeCore Internet MPLS Node


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INPUTS

BUFFER

MANAGEMENT

OUTPUT

BUFFER

Switch Control

Processor

Switch Control

Processor


OUTPUTS

ATMATM

STM-1/4/16

STM-1/4/16

Smart Connections

Pre-computation

PNNI routing

PNNI signaling

OSPF(TE), IS-IS(TE), BGP4

RSVP-TE, CR-LDP

Policing

Marking

IP Forwarding

Labeling

Classification

Buffer

Allocation

Packet Drop

Per Port

Per Priority

Per Flow

Queuing

Flow

Merging

Hierarchical

Scheduler

Shaper

10-40G

Fabric(s)

STM-1/4/16

STM-1/4/16

POSPOS

Edge ATM/Label Switch RouterEdge ATM/Label Switch Router

STM-1/4CH STM-1/4CH

ATM

ATMATM


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SummarySummary

Traffic Engineering ina Best Efforts IPnetwork

Traffic Engineering ina Multi-service IPnetworkThe design of a Label

Switched Router

Traffic engineering placesthe traffic where thenetwork is, maximizingrevenue from a givencapacity network

It enables the support ofpremium services

Premium servicesgenerate the mostprofitability.

MPLS is a key technologyin building a profitableNew Public Network


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For more informationFor more information

Marconi is a $10B revenue, 45,000 employee globalTelecoms supplier that has world class expertise at alllevels of constructing the New Public Network Access (optical and copper)

Transport (SDH SONET and DWDM) Switching and Routing (IP, MPLS, ATM,) Voice and Intelligent Network software Systems design installation and operation

Marconi web site is at www.marconi.comOr contact me David Drury [email protected]
http://www.marconi.com/http://www.marconi.com/


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Thank youThank you

David Drury

[email protected]

traffic engineering in large ip networks with mpls

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