RoutingandSpectrumAllocationforMulticastTrafficinElasticOpticalNetworks

Presenter: AnliangCAISupervisor: Prof.MosheZUKERMANCity University of Hong Kong1February2018

Supported by a grant from RGC of HK SAR (CityU 11216214)

Outline

ØIntroductionØOptimalProvisionofaMulticastDemandØLight-Tree-BasedEONDesignØProvisioningMulticastinEONwithSharedProtection

ØConclusions

2

Introduction – Traffic Increase

3

Bigdata Cloudcomputing UHDvideo Virtualreality

Rapidtrafficgrowth– Zettabyteera• AnnualglobalIPtrafficwillreach2.3

Zettabytesby2020• Compoundannualgrowthrate:22%

Credit: http://www.pacsquare.com/; https://www.pinterest.com/; http://www.alphafinity.com/; Cisco, “Cisco visual networking index: Forecast and methodology, 2015–2020,” 2016.

Introduction (Cont.)• Diversetraffic• Elastic optical networks(EONs)

– Flexible frequency grid– Better spectrum utilization– ……

4M. Jinno et al., IEEE Commun. Mag., 48(8), pp. 138-145, 2010.K. Christodoulopoulos et al., J. Lightw. Technol., 29(9), pp.1354-1366, 2011.

Frequencyslot(FS):A unittoquantizethespectralresources

Elastic

frequency

WDM

frequencyw1 w3w2

Bandwidth saving

50 GHzExsiting ITU-T fixed grid

New flexible grid

100 Gbps

10 Gbps

40 Gbps

50 GHz 50 GHz

50 GHz

30 GHz

10 GHz

Spectrumresourcesinopticalfibers

Routing & Spectrum Assignment (RSA)• Routing– findapath,e.g.,byDijkstra’salgorithm• Spectrumassignment

– Spectrumcontinuity:assignsameFSsinalltraversedlinks– Spectrumcontiguity(𝑓", 𝑓$ not𝑓", 𝑓%)– Spectrumnon-overlapping:any FSina fibercannotbeallocatedtotwoor

moreconnections

5

Optical fiber

BVT

BV-OXC

IP router

Node B

Node C

Node D

Node ABVT: Bandwidth-Variable TransponderBV-OXC: Bandwidth-VariableOptical Cross Connect

Lightpath2:BàC

…

…

f6f7

Lightpath 1: AàC

f1f2f3

f1f2f3

Lightpath:anopticalchannelbetweentwonodes

Overview• DesignanEONwithprotectionformulticast

– Comparethreetechnologiesforprovisioningmulticast– ProposeefficientheuristicalgorithmtodesignEONs– Extendthenetworkdesignwithprotection

• Problemstatement– Given:anetworkandmulticasttrafficdemand(s)– Objective:minimizenetworkresourceusage

• Methodology:mixedintegerlinearprogramming(MILP)formulationandheuristicalgorithm

6

OutlineØIntroduction

ØOptimalProvisionofaMulticastDemand

ØLight-Tree-BasedEONDesignØProvisioningMulticastinEONwith SharedProtection

ØConclusions

7

Optimal Provision of a MulticastDemand• Multicasttraffic:data transmittedfromonesourcetomultipledestinations,e.g.,𝐴 → 𝐵, 𝐶, 𝐸

• Bandwidth-intensive multicastservices– UHD TVdelivery,inter-datacentersynchronization,video conferencing,etc.

8

ASource

C Destination2

E Destination3

F

BDestination1

D

1

5

3

0

4

9

6

2

8

10

7

InterDatacenterNetwork

Provisioning Technologies for Multicast• Lightpath:separatelightpaths todestinations• Light-tree:extensionoflightpath – viaatreestructure,tree

nodescanreceivesignalcopies• Light-trail:extensionoflightpath – viaatrailstructure,trail

nodescanreceivesignalcopies

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I. Chlamtac et al., IEEE Trans. Commun., 40(7), pp. 1171—1182, Jul. 1992.L. H. Sahasrabuddhe and B. Mukherjee, IEEE Commun. Mag., 37(2), pp. 67–73, Feb. 1999.A. Gumaste and I. Chlamtac, IEEE HPSR, 2003, pp. 251–256.

Lightpath Light-tree Light-trail

source

destination

Distance-Adaptive Transmission (DAT)• Transmissions of shorter paths

can use higher level Modulation Schemes (MSs)

• For a given data rate, the higher level the modulation, the less bandwidth requirement

• For a light-tree/light-trail, MS assignment is subject to the longest distance among the transmissions to all destinations

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K. Christodoulopoulos et al., J. Lightw. Technol., 29(9), pp.1354–1366, 2011.C. Wang et al., J. Lightw. Technol., 33(14), pp. 2955–2964, 2015.K. Walkowiak et al., IEEE Communi. Lett., 18(12), pp. 2117–2120, Dec. 2014.

DATModelModulationScheme

TransmissionDistance

CapacityperFS

BPSK 4000 12.5Gb/s

QPSK 2000 25Gb/s

Example:40-Gb/sconnections

3

1

2

5

4

6

1200

1500

1500

1200

1200

1200

1200

1200

2700 km

1200 km

BPSK

QPSK

1200 km 2700 kmMustchooseBPSK

L4 L3 L2 L1….

L1>L2>L3>L4>….….

BPSKQPSK8QAM16QAM

Modulation Level

Transparent Reach

Lightpath Technology with DAT• Example:𝐴 → 𝐵, 𝐶, 𝐷 requesting30Gb/s• Lightpath scheme:separatelightpaths formulticast

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Optical Fiber

BVT

Client

Lightpath 2

Lightpath 1

Node B

Node C

Node D

Node A

BVT: Bandwidth-Variable TransponderBV-OXC: Bandwidth-Variable

Optical Cross Connect

Lightpath 3

BV-OXC

Usage:3transmitters8FSs

8QAM

BPSK

8QAM

Light-Tree Scheme with DAT• Asinglelight-tree

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Optical Fiber

BVT

MC-OXCClient

Light-tree 1

Node B

Node C

Node D

Node A

BVT: Bandwidth-Variable TransponderMC-OXC: Multicast-Capable

Optical Cross Connect

Usage:1transmitter9FSs

Notnecessarilymorespectrumefficientthanthelightpath scheme

BPSK

Multi-Light-Tree Scheme with DAT• Multiplelight-trees

13

Optical Fiber

BVT

ClientLight-tree 2

Light-tree 1

Node B

Node C

Node D

Node A

BVT: Bandwidth-Variable TransponderBV-OXC: Bandwidth-Variable

Optical Cross Connect

MC-OXC

Usage:2transmitters7FSs

BPSK

8QAM

Light-Trail Scheme with DAT• Asinglelight-trail

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Optical Fiber

BVT

Client

Light-trail 1

Node B

Node C

Node D

Node A

BVT: Bandwidth-Variable TransponderMI-OXC: Multicast-Incapable

Optical Cross Connect

MI-OXC

Usage:1transmitter12FSs

BPSK

Multi-Light-Trail Scheme with DAT• Multiplelight-trails

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Optical Fiber

BVT

ClientLight-trail 2

Light-trail 1

Node B

Node C

Node D

Node A

BVT: Bandwidth-Variable TransponderMI-OXC: Multicast-Incapable

Optical Cross Connect

MI-OXC

Usage:2transmitters7FSs

BPSK

8QAM

Results – Six-Node Networks• Transmitterusage:lightpath ≥multi-light-trail≥multi-light-tree≥ light-tree= light-trail

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3 4

1 2

5 6

3 4

1 2

5 6

3 4

1 2

5 6

Results – Six-Node Networks (Cont.)

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3 4

1 2

5 6

3 4

1 2

5 6

3 4

1 2

5 6

Results – Real-Size Networks• Multi-light-tree,multi-light-trail,light-treeschemesshowcomparableperformance,whilelight-trailistheworst,lightpath liesinbetween

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COST239 USNET

Running Time

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Comparison of CPU Times in Units of Seconds by the Five Schemes in the USNET Network

Comparison of CPU Times in Units of Seconds by the Five Schemes in the COST239 Network

Benefit of DAT• Moresavingswithhighernetworkdensity• Lightpaths receivethemostsavingsforthehighestmodulationgain

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Spectrum Savings of Distance-Adaptive Spectrum Allocation for a Multicast Demand

OutlineØIntroductionØOptimalProvisionofaMulticastDemand

ØLight-Tree-BasedEONDesignØProvisioningMulticastinEONwith SharedProtection

ØConclusions

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Light-Tree-Based EON Design• Thelight-treescheme:satisfactoryperformanceinreal(sparse)networks

• Multiplemulticastdemands• Objective:minimizethemaximumspectrumrequiredinthelinks

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Optical fiber

BV-T

MC-OXC

IP routerLight-tree 1: Aà{C,D}

f8f9

Node B

Node C

Node D

Node A

f8f9

f8f9

Light-tree2:Bà{C}

f1f2f3 ……

Heuristic Algorithm• MILPisnotscalable,butforreal-sizeproblemswestillneedtominimizethespectrum.

• Weproposepolynomial-timeheuristicalgorithm,i.e.,DCMCT,andcompareittotheexistingalgorithms,namely,AFAandshortestpathtree.

• DCMCTaimsforahigher-levelMS– Higher-levelMS->fewerFSsperlink– Higher-levelMS->shorterreach ->shorterpath->smallertrees->fewerFSsintotal

– Butwemayneedlongerpath->lower-levelMS->currentresourcescanbereused

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Demand-Serving Order Matters!• Inourheuristicalgorithm,i.e.,DCMCT,weservethedemandsinanorder. Differentdemand-servingordersyielddifferentresults.

• Threeorderingmethods– _DO:arrangedemandsindecreasing orders– _n: Shufflethedemandstoobtainarandomlyorderedsequence.Tofurther improvethesolutionquality,weconsiderndemandsequencesforeachset

– _n_DO:nshuffledsequenceseachorderedby_DO24

DCMCTalgorithm

Input OutputAdemandsequence Result

r1

r2

r=min ri

D1D2D3D4D5S1

D3D4D5D1D2S2

Results – n6s9• Theeffectofthenumberofdemandsequencesontheheuristicperformance

• Gap totheoptimum: _1k(3%),_10k(1.8%)• 1,000demandsequences->sufficientlygood

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Results – n6s9 (Cont.)• DCMCT_1kisclosetotheoptimumandoutperformstheotheralgorithmsincludingtheexistingone

26

Results – Real-Size Networks• Undercomparablerunningtime,DCMCT_y_DOperformsthebest

• Onaverage,AFAperformstheworst– Requiring11.7%(COST239),16.7%(USNET)morespectrumthanDCMCT_y_DO

– WorsethanDCMCT_DO(tensofmilliseconds)

27COST239 USNET

Results – Comparison Between DCMCTand Shortest Path Tree (SPT)• DCMCToutperformsSPTforallthecases

28

COST239 USNET

OutlineØIntroductionØOptimalProvisionofaMulticastDemandØLight-Tree-BasedEONDesign

ØProvisioningMulticastinEONwith SharedProtection

ØConclusions

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Provisioning Multicast in EONs withShared Protection

• A link failure (e.g., a trunk of a multicast) couldresultinsevereservicedisruption

• Protection– enablenetworkstocontinuetooperateunderafailure

• Focus:single-linkfailure(dominantscenario)

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1

2

3

4

5

6

Source Destination

Shared Protection Scheme• Protectalight-treebyhavingeachofitsprimarypathsprotected

viaalink-disjoint backuppath– Link-disjoint:Nobackup path shares common link with itsprimarytree– Self-sharing(SS):The resources in alink allocated to a source-destination

pairprotectthe primary path of anotherSDpair

• Cross-sharing(XS):Multiple connections can share backup-onlyresources as long as they do not fail simultaneously

Anexampleforprotectionschemes:(a)afour-nodefully-meshnetwork;(b)link-disjoint;(c)self-sharing;and(d)cross-sharing.

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A

D

B

C(b) M1: A->{B,C}

B

C D(c) M2: B->{C,D}

A B

DC(d) M1&M2

Primary-only link

SS linkSS link

Backup-only link

XS link

Physical linkA

D

B

C(a) A four-node fully-mesh network

N. K. Singhal et al., Comput. Netw., 50(2), pp. 200-206, 2006.

Results – n6s9• Compared to the MILP, we propose polynomial

time heuristic, i.e., APPF_G – APPF_G_DO requires 11.8% more spectrum– APPF_G_100 requires 4.4% more spectrum

• 100randomsequencesareconsideredsufficienttoachievenearoptimum

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Results – COST239• APPF_G_4000savesonaveragearound9%spectrumcomparedtoAPPF_G_DO

• 4000randomsequencesachievenearperformanceto10000sequences,andareconsideredsufficient

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Results – USNET• Ourproposedalgorithmoutperformsthestraightforwardmethod

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OutlineØIntroductionØOptimalProvisionofaMulticastDemandØLight-Tree-BasedEONDesignØProvisioningMulticastinEONWithSharedProtection

ØConclusions

35

Conclusions• Wecomparedthefiveschemesformulticastprovisioning– MILPformulationforthelight-trailtechnology– EvaluatedthebenefitofDATforthefiveschemes

• Wedesignedalight-tree-basedEON– AMILPformulationandanefficientheuristicalgorithm– Theproposedheuristicoutperformstheexistingones

• Weextendedthenetworkdesignwithprotection– Firstworkofthisimportantproblem– MILPformulationandheuristicalgorithm

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