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Planning SwitchedOptical Networks

Tivadar Jakab, Zsolt [email protected]

Budapest University of Technology and Economics

Department of Telecommunications

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4/8/03 Third Hungarian WDM Workshop 2

Outline

Network planning: Traditional approaches and newchallenges

Planning dynamic networks: Requirements and

solutions Network resilience: Service and operational

considerations

Illustrative numerical examples

Summary and conclusions

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Network Planning

Planningprocess

Service demands Available technologiesand equipment

Business considerations

Co-operation

requirements

Technical

constraints

Current network

Optimalnetwork

plan

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Traditional Network PlanningApproaches

Services

Forecast

Demands

Planning

Network extension

Emerging new services

Modelling and forecasting

difficulties

Uncertainties

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Planning Approaches for DifferentTime ScalesLTP demandforecast T0

Installedplan T0

T0 T1 T2 T3 T4

a) Long-term planning approach

b) Medium-short term planning approach

Installedplan T0

T0 T1 T2 T3 T6T4

Target LTPplan T0

ST-MTplan T0

ST-MTplan T1

ST-MTplan T2

New long term planning processSTP-MTP

demand forecastT0

. . . . .

Installedplan T2

T6

. . . . .

Target LTPplan T2

Long term planning process

T0-T4

LTP demandforecast T2 Long term planning process

T2-T6

LTP planT0

LTP planT2

Medium-short term planning process

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New Challenges in NetworkPlanning

Soft-permanent OCh services More dynamic networks

Client traffic (IP) modelling and forecasting

difficulties Sharp competition

Strict economical conditions

How to save money? How to make money?

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Planning Dynamic Networks:Requirements

Flexibility Manageability

Fast provisioning

Advanced resilience

Service differentiation

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Planning Dynamic Networks:Solutions

Network

Real-time traffic control

Configuration management(Traffic management and resourceconfiguration)

Network planning, and development

(Traffic and transport)

Network operation, management and planning

Measured traffic data

Link capacities(Traffic and transport)

Routing strategy

(Traffic and transport)

Months - years

Days - weeks

Minutes - seconds

Traffic

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Planning Dynamic Networks:Solutions

Optimal

network extension

Network consolidation

Rearrangements to achieve

the optimal configuration

Provisioning

Network configuration

to serve dynamic requests

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Illustrative examples (1)Penalty on Dynamic Behaviour 2/1

Permanent channel requestsarriving randomly in time and

space

A simple distribute control

mechanism is to decide on

connection set-up

Routing: shortest path based

Wavelength assignment:

sequential (first fit)

Connection set-up is based onlocal, sub-optimal decisions

(requests should be served -

minimal blocking)

All channel requests areknown in advance

Pre-planned path selection

and wavelength assignment

Routing: shortest path based

Wavelength assignment: after

path selection (fixed route)

Optimal solution (targetfunction: minimal resource

need)

Dynamic Network Theoretical optimum

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Network example:Hypothetical Hungarian Backbone

Network structure:

9 nodes, 16 links

average nodal degree: 3.5

Demand pattern:

Heavy star + light mesh

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Illustrative examples (1)Penalty on Dynamic Behaviour 2/2

0

500

1000

1500

2000

2500

3000

Dynamic Pre-planned OTN

Network Type

OCh*h

op

Extra OCh to be installedOCh in use

Same routing

without effective

capacity constraints

(simplified case)

30% penalty on

dynamic behaviour

Evaluation of examples based

on link characteristics:

number of channels in use

number of channels to be

installed w/o WLS

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Illustrative examples (2)

A More Perspective Case - Penaltyon Dynamic Switching

Automatically Switched Optical Network Switched OCh service

Illustration of potential statistical gains (traffic

concentration) and penalties on dynamic behaviour Switched optical channels based service for on-

demand connection requests

Instead of providing leased lines result in statisticalgains for the operator

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Automatically Switched OpticalNetworks - ASON

Based on advanced signalling (GMPLS) and switchingcapabilities which facilitate the introduction of intelligentflexibility and distributed management into optical networks

Optical

switch

Transport plane

PI

OCC Control plane

NNI

CCI

Clientequipment (IP

router, ATMswitch, )

OCC

Optical

switch

PI

UNI

NMI-T

NMI-A

Optical

switch

OCC

EM/NM

Managementplane

Optical

switch

Transport plane

PI

OCC Control plane

NNI

CCI

Clientequipment (IP

router, ATMswitch, )

OCC

Optical

switch

PI

UNI

NMI-T

NMI-A

Optical

switch

OCC

EM/NM

Managementplane

CCI: Connection Control Interface

NMI-A: Network Management Interface for the ASON Control Plane

NMI-T: Network Management Interface for the Transport Network

NNI: Network to Network Interface

OCC: Optical Connection Controller

PI: Physical Interface

UNI: User to Network Interface

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Comparison Model On-off sources:

permanent connection in OTN case

switched connection in ASON case

A pont

B pont

C pont

D pontA pont

B pont

D pont

ton1 toff1 ton2

B2 forrs

Time ton1 toff1 ton2

B2 forrs

Time

OTN with permanent connections ASON with switched connections

C pont

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OTN penalty for WLA

without WLC (about 60%)

Statistical gains due to switching

below 0.7 source activity ratio

Higher penalty for dynamic WLA

without WLC (about 100%)

Statistical gains from

protected switchedOCh based services

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Statistical gains from protectedswitched OCh based servicesSource activity ratio

25%

Onlyswitched OCh

Only

permanent OCh

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Statistical gains from switchingin case of mixed services

0

500

1000

1500

2000

2500

3000

3500

4000

4500

"75:25""50:50""25:75"OTN 0:100

permanent

onlySwitched

to permanent rate

OCh*hop

Och to be installed

Och in use

Different switched to permanent rate

(switched with 25% source activity ratio)

100:0

switched onlyIncreasing rate of switched traffic

100% 100% 87% 75% 57% 44%

100% 112% 97% 82% 58% 46%

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Network Resilience Dynamic application of extra network

resources to limit the impact of failures Based on dedicated or shared network

resources

Requires switching function to be supportedin nodes

Basic schemes: 1+1 dedicated protection

n:m shared protection

restoration (dynamically configured shared capacities)

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Resilience in Full FlexibleNetworks

0%

50%

100%

150%

200%

250%

300%

not

prot.

optimal

path

rest.

1+1

Resilience Cases

RelativeHop*OCh

Extra for resilienceWorking

0%

50%

100%

150%

200%

250%

300%

not prot.

full flex.

1+1 term.

switch.

1+1 full

flex.

optimal

path rest.

full flex.Resilience Cases

Relative#SwitchPort

sExtra due to resilience

Working

Full flexible network: each capacity unit terminates onswitching-capable node equipment (e.g. flex. OADM

or OXC)

Comparison of link capacities Comparison of switch capacities

Extra for

dedicated

resilience

Savings on

capacitysharing Switches

not used

for resilience

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Network ResilienceService Considerations

Different applications may need resilience withdifferent characteristics, such as

recovery speed

rate of recovered capacity (partial/entire) Different resilient classes can be specified

according to the different needs

Aim: meet different resilience requirements on thesame technical basis and lowest cost

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Restoration with Tailored RecoveryTime

Recovery time is assumed to be proportional with thenumber of active switching nodes involved in theprocess

Some switches can be pre-set and fixed to speed upthe recovery process

Reduced flexibility results in less efficient capacitysharing, therefore the amount of extra resources forrestoration is increasing

The joint optimisation of different classes may reducethe penalty

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Restoration with Tailored RecoveryTime

Impact of Tailored Recovery Time

on Network Configuration

0%

20%

40%

60%

80%

100%

Case 0 Case 1 Case 2 Case 3 Case 4 Case 5

Service Class Cases

Rateoflogicalhopswith

differentnumberofpre-set

switches

4 pre-set switch

3 pre-set switch

2 pre-set switch

1 pre-set switch

0 pre-set switch

Impact of Tailored Recovery Time

on Network Resources

0

50

100

150

200

250

300

350

400

450


Service Class Cases

R

esourceNeeds[OCh*hop]

spare for resilience

working

Average hop count of recovery paths

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00


Service Class Cases

Averagehopcount

Traditional

restoration

1+1dedicated

protection

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Network ResilienceOperational Considerations Guaranteed Capacity Optimal Restoration (traditional)

centralized management, explicit routing

Minimal Route Restoration

fits to the distributed environment - easy to implement

Disjoint Route Restoration

source routing

simple to return to the working route after clearing the failure

1+1 Dedicated Path Protection

source routing

Shared Path Protection

source routing, at least 3-connectivity of the network structure isrequired

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Restoration with DifferentOperational Options

0

200

400

600

800

1000

1200

1400

1600

1800

2000

NotProt Capac. Opt.

Rest

Min. Route

Rest

Shared PP 1+1 Disj. Route

Rest.Protection Options

TotalOC

h*hop

extra # channels toimplemented the

network w/o WLC

#channels in use

100% 91% 113% 131% 139% 149%

100% 140% 242% 203% 248% 257%

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Summary and Conclusions

The impact of intelligent switching capabilities onthe planning of dynamic optical networks has beenoverviewed

Network resilience has been studied taking into

account service and operation orientedconsiderations

Some small numerical examples have been

presented to illustrate the presented planningapproaches

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Related Publications

T. Jakab, Zs. Lakatos: Protection and restoration based resilience in Automatic Switched Optical

Networks, Proceedings of NETWORKS 2002, Munich, Germany, June 2002, pp. 459-467 T. Jakab: 4.3 Network Planning in TELECOMMUNICATION NETWORKS AND INFORMATICS

SERVICES Chief Editor: dr Gyrgy Lajtha, http://www.hte.hu/ob/eng/4.pdf, Scientific Association forInfocommunications (HTE), 2002.

T. Jakab, Zs. Lakatos: Protection or restoration: a generic study on the impact of line costs andswitching costs on the strategic decisions, Proceedings of DRCN2001, June 2001, Budapest, Hungary

T. Jakab, R. Clemente, C. Mas, H. Nakajima: Techno-economical analysis of ASON: Comparison of

resilience options - First Results from EURESCOM FASHION Project, Proceedings of DRCN2001,June 2001, Budapest, Hungary

T. Jakab, Zs. Lakatos: Protection or restoration: a generic study on the impact of line costs andswitching costs on the strategic decisions, Magyar Tvkzls (Hungarian Telecommunication Journal),XII. (2001), Selected Papers

EURESCOM P1012 FASHION Project Publications http://www.eurescom.de/public/projects/P1000-series/p1012/default.asp

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