“issues and challenges in physical-layer aware optically switched network design and...

16 Sep'09 Int. Conf. on Photonics in Switching 2009 1

www.ait.edu.gr

“Issues and Challenges in Physical-Layer Aware Optically Switched Network

Design and Operation”

“Issues and Challenges in Physical-Layer Aware Optically Switched Network

Design and Operation”Yvan Pointurier, Siamak Azodolmolky, Marianna Angelou and

Ioannis Tomkos{yvan,sazo,mang,itom}@ait.edu.gr

http://www.ait.edu.gr

ATHENS INFORMATION TECHNOLOGYATHENS INFORMATION TECHNOLOGY

September 15-19, 2009 – Pisa, Italy

Session: “Impairment Aware and Reconfigurable Optical Networks”

WeII3-1

http://www.ait.edu.gr/


www.ait.edu.grOutlineOutline

• Introduction• Motivations• Issues and design challenges• DICONET framework• Impairment aware lightpath

establishment• Conclusions



www.ait.edu.grIntroductionIntroduction

• Evolution of core optical networks:– Past, Present, Future!

Optical-bypass



www.ait.edu.grKey challengesKey challenges

• Physical Impairments accumulation– Signal impairments accumulate along a

transparent optical path, therefore limiting the system reach and the overall network performance

Impairment aware routing and wavelength assignment algorithms

• Failure localization– Failure propagate in a transparent network

environment and they can not be easily localized and isolated.

• Control plane integration – What to monitor and distribute?– What is the best control plane integration model?



www.ait.edu.grToward Future Core Optical NetworksToward Future Core Optical Networks

• The network evolution aims at:– Improved cost economics (less costly electronics)

• Cost savings of a transparent solution over an opaque network design of up to 50% could be achieved

– Source: M. Gunkel, et. al. “A Cost Model for WDM Layer”, Photonics in Switching Conference, 2006.

– Reduced investment and operations Efforts (CAPEX, OPEX)

– Scalability (bit rate independence)– Suitability to future services (e.g. Grid computing)

• The main drivers for network architecture migration:– High bandwidth and end-to-end QoS guaranteed services– Dynamic (on demand) technology-independent service

provisioning



www.ait.edu.grDICONET framework (1/2)DICONET framework (1/2)

• Cross-layer optimization– Physical layer impairment monitoring/management– Impairment Aware Lightpath Routing (a.k.a. IA-RWA)

• The main Idea:– The development of a dynamic network

planning/operation tool residing in the core network nodes that incorporates real-time measurements of optical layer performance into IA-RWA algorithms and is integrated into a unified control plane.

http://www.diconet.eu



www.ait.edu.grDICONET framework (2/2)DICONET framework (2/2)

•Physical Layer Impairments modeling•Optical Performance and Impairment Monitoring•IA-RWA (Lightpath routing)•Intelligent Component placement algorithms•Failure localization and resilience algorithms•Control plane integration



www.ait.edu.grDICONET NPOT: Key building blocksDICONET NPOT: Key building blocks

• Network Planning and Operation Tool (NPOT)



www.ait.edu.grPhysical layer performance evaluationPhysical layer performance evaluation

• In the context of transparent optical networks impairment can be categorized into “static” (e.g. ASE noise, PMD, filter concatenation) and “dynamic” (network-state dependent: e.g. node crosstalk, XPM, FWM) impairments.

• We utilize a “Q-Tool” to assess the QoT of a lightpath. Q-Factor for a lightpath is a QoT indicator that is related to the signal’s BER.



www.ait.edu.grInaccuracy of the Q-Tool (1/2)Inaccuracy of the Q-Tool (1/2)

• Practical QoT estimators (including our Q-Tool) is a combination of analytical models and/or interpolations of measurements and simulations.

• Practical QoT estimators should be fast in order to support quick lightpath establishment.

• Inaccuracy of Q-Tool– Imperfect physical models (by nature)– Optimization for speed

• Incorrect QoT estimation has a direct impact on lightpath establishment– Q overestimate accept LP with inadequate QoT– Q underestimate block LP with adequate QoT



www.ait.edu.grInaccuracy of the Q-Tool (2/2)Inaccuracy of the Q-Tool (2/2)

40%

(η=1)



www.ait.edu.grOnline “Rahyab” (1/4)Online “Rahyab” (1/4)

• The main idea behind online Rahyab algorithm is to design a multi-constraint IA-RWA algorithm that considers QoT inaccuracy through optical monitor availability information in routing decisions, in order to alleviate the inaccuracy of the QoT estimator (i.e. Q-Tool).

• “Rahyab” building blocks– Multi-Constraint Path (MCP) computation

framework• Link cost vector and Single Mixed Metric Mapping

– Online “Rahyab” flowchart




• Considering a network topology G=(V,E), each link ‘e’ is characterized by M additive non-negative weights, wm(e), m=1,2,…,M. Given constraint Cm,m=1,…,M, the MCP problem is to find a path p such that:

• Single Mixed Metric (SMM) (insight: can meet all Cm with high prob. using simple shortest path alg. on weighted graph):




• Link cost vector (2 costs, can be extended):– Metric: link length L(e)

Constraint: max lightpath length: L<LMax

– Metric: impact of inaccuracy (on QoT estimator) based on monitor availability (mi) for a given link e: Θ(e).Constraint: max inaccuracy over a lightpath: η<ηmax



www.ait.edu.grFlow diagram of RahyabFlow diagram of Rahyab

W=w

W=w-1

W=1

Find “K” path using the MCP Engine



Candidate Lightpath(s)

Active Lightpath(s)(Currently established)

“Mirror”

QoT EstimatorAnd Impact estimation

Lig

htp

ath

wit

h

leas

t im

pac

t

Useable Lightpath(s)

Active Lightpath(s)(Currently established)



www.ait.edu.grSimulation SetupSimulation Setup

• DTNet– Number of nodes:14– Number of links:23– Average node degree:3.29– Diameter: 800 km Hamburg

BerlinHannover

Bremen

Essen

Köln

Düsseldorf

Frankfurt

Nürnberg

StuttgartUlm

München

LeipzigDortmund



www.ait.edu.grResults (1/3)Results (1/3)

• Blocking rate vs. load




• Blocking rate vs. channels/link




• Required channels/link to reach 0% blocking rate



www.ait.edu.grFast lightpath establishmentFast lightpath establishment

• Different approach: incorporate additional (“historic”) probing data to make better QoT estimation

• Setup: when demand arrives: a) estimate QoT using past monitoring data (probes), b) send probe

• Problem: wrong QoT estimation leads to additional LP establishment attempts, which should be decreased for fast lightpath establishment

• Proposed solution: – Perform QoT estimation for LPs - use monitoring data of LPs

already established – Use “end-to-end” estimation framework (“network kriging”):

leverage correlation between LP QoT, induced by topology• Lightpaths using common links sustain similar physical effectsWork with Nicola Sambo et al., ICTON 2009

(BONE)



www.ait.edu.grPrinciple Of Network KrigingPrinciple Of Network Kriging

• End-to-end estimation framework [Chua, Kolaczyk, Crovella, JSAC 2006]• Solves the following problem:

– Given additive metric y s.t. y=Gx

• =end-to-end (lightpath) metric, =routing matrix, x=link metric

• OB: observed lightpath/metric, UN: unobserved• Typical example: x=link delay, y=route delay, G(i,j)=1 if link j is on route i,

G(i,j)=0 otherwise – Given the observed (with probing) end-to-end metrics (for some of the

routes) yOB – Compute the end-to-end metric y for all routes (and in particular for yUN)

– We will exhibit the real physical meaning of y soon

Example• Suppose LP1, LP2, LP3 established and monitored• LP4 demand arrives: QoT>QoTthreshold?

• Can estimate ŷ4 given y1, y2, y3 and determine QoTLP4

• Estimation technique = “network kriging” [JSAC 2006]

ŷUN=GUNGOB(GOBGTOB)+yOB

UN

OB

y

yy

UN

OB

G

GG



www.ait.edu.grQoT modelQoT model

• Use QLP=f(OSNR(LP), CD(LP), PMD(LP), φ(LP))• QoT model account for ASE, PMD, CD, SPM

(φNL) – OSNR: OSNR-1 is additive

1/OSNR(LP)=1/OSNR(l1)+1/OSNR(l2)– CD: dispersion is additive (in ps/nm) – PMD: PMD2 is additive (in ps2)– φNL: nonlinear phase is additive (in rad)

• Can use power monitor to measure it

• Need 4 types of monitors (OSNR, CD, PMD, φNL)

Perform estimation on y={1/OSNR, CD, PMD2, φNL}



www.ait.edu.grSupport through PCE architectureSupport through PCE architecture

• Assume all 4 kinds of monitors are available at all nodes

• Existence of a centralized measurement database MD where measurements from all previous monitored LPs is recorded

• LP establishment: source queries MD to estimate QoT of candidate

• If QoT acceptable: – probing – destination updates MD

Upd

ate

MD

: LP

4=

(OS

NR

4, C

D4, P

MD

4, φ

4)

s

d

MD

LP1: (OSNR1, CD1, PMD1, φ1)LP2: (OSNR2, CD2, PMD2, φ2)LP3: (OSNR3, CD3, PMD3, φ3)LP4: (OSNR4, CD4, PMD4, φ4)

LP4QoT(LP4)

Estimated QoT>QoTthreshold

Establish LP4



www.ait.edu.gr

Simulation results: Reduction in setup attemptsSimulation results: Reduction in setup attempts

• Pan-European topology, 17 nodes, 2x32 links, 40 W/direction

• C-NKS: with network kriging; C-MDS: without

• n=number of attempts to establish a lightpath

• For same blocking rate, gain 1 attempt in averageSame blocking rate

≈ 2x10-3

Without estimation (MDS): 2 attempts to

establish lightpath

With estimation (NKS): 1 attempt

needed to establish lightpathSource: Nicola Sambo, et al., ICTON 2009



www.ait.edu.grSimulation results: dynamic behaviorSimulation results: dynamic behavior

x-axis: time

With end-to-end estimation: faster convergence of blocking rate hints at a higher resilience of the technique to network changes (failure, etc)

Source: Nicola Sambo, et al., ICTON 2009



www.ait.edu.grConclusionsConclusions

• Next Generation Core Optical Networks– Many studies around– Many problem addressed– Not many integrated and comprehensive works

• DICONET Integrated Network Planning and Operation Tool– Presented here: Lightpath establishment with consideration for Q-Tool

inaccuracy, fast lightpath establishment

• Future work/Work in progress:– Fault detection/management– Control plane design and implementation– Integrated planning and operation tool– FPGA acceleration of Q estimator– Validation with test-bed



www.ait.edu.grThank you!Thank you!

• Question & Answers

• Acknowledgements– This work is partially funded by the European Commission (FP7)

Building the Future Optical Network in Europe

http://www.ict-bone.eu

Dynamic Impairment Constraint Networking for Transparent Mesh

Optical Networks

http://www.diconet.eu


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