light paths

8/3/2019 Light Paths

1/27

Optical NetworksBM-UC Davis 122

Part III

Wide-Area (Wavelength-Routed)

Optical Networks

1. Virtual Topology Design

2. Wavelength Conversion

3. Control and Management


2/27


Lightpaths and Wavelength Routing

Lightpath

Virtual topology

Wavelength-continuityconstraint

Wavelength conversion

Packet routing


3/27


Illustrative example

WA

CA1

CA2

UT

CO

TX

NEIL

MI

NY

NJPA

MD

GA


4/27


Solution 1a: Infocom94 and ToN-Oct96

More than one laser filter pair at any node can tune to the samewavelength


5/27


Solution 1b: Infocom94 and ToN-Oct96

All laser filter pairs at any node must be tuned to differentwavelengths


6/27


Virtual Topology


7/27


Wavelength Routing Switch (WRS)Details of the UT Node


8/27


Optimization Problem Formulation

On virtual topology connection matrix Vij

iTV ij

ij jRV j

i

ij

On physical route variablespijmn

mn

ij

mn Pp

ij

ij

mn Vp

jikifppn

ijkn

m

ijmk ,

ij

n

ij

in Vp

ij

m

ij

mj Vp

On virtual topology traffic variables sdij

0sd

ij

sd

j

sd

sj

sd

j

sd

sj

dskifj

sd

kj

i

sd

ik,

CVij

ds

sd

ij

,

On coloring of lightpaths cijk

ij

k

ij

k Vc

knmcp ijk

ij

ij

mn,,1

Objective: Optimality criterion(a) Delay minimization:

(b) Maximizing offered load (equivalent to minimizing maximum flow in a link):

ij sd mn sd

sd

ij

mn

ij

mn

sd

ijC

dpMinimize

1

jisd

sd

ij ,maxmin

New optimality criterion

(c) Minimize average hop distance

ji ds

sd

ij

ds sd

Minimize, ,,

1


9/27


Solution Approach to Virtual Topology WDM WAN Design

1. Choice of optimal virtual topology Simulated annealing; optimization based on maximizing throughput,

minimizing delay, maximizing single-hop traffic, etc.

2.Routing of lightpaths over the physical topology Alternate-path routing, multicommodity flow formulation, randomized

routing

3. Wavelength assignment: Coloring of lightpaths to avoidwavelength clashes

Graph-coloring algorithms, layered graph models

4. (Optimal) routing of packets over the virtual topology

Shortest-path routing, flow-deviation algorithm, etc.

5. Iterate

Check for convergence and go back to Step 1, if necessary.


10/27


Details of Virtual Topology Design

Simulated Annealing

Start with random virtual topology Perform node exchange operations on two random nodes

Route packet traffic (optimally) using flow deviation

Calculate maximum trafficscaleup for current configuration

If maximum scaleup is higher then previous maximum,then accept current configuration;else accept current configuration with certain decreasing probability

Repeat until problem solution stabilizes (frozen).

Flow Deviation

Perform shortest-path routing of the traffic

Select path with large traffic congestion Route a fraction of this traffic to less-congested links

Repeat above two steps iteratively, until solution is acceptable


11/27


NSFNET Traffic Matrix (11:45 PM to midnight, ET, Jan. 12, 1992)


12/27


The WDM Advantage

Transceivers/node

Scaleup

4 106

5 1356 163


13/27


Delay Components in a WDM Solution


14/27


Scaling of Bandwidth The WDM Advantage

No WDM (Physical Topology)

Mbpsp

p

pH

CL

WDM (with P transmitters/receivers per node)

Mbpsvv

vv

HCNP

HCL

WDM Advantage

vp

v

v

p

pv

p

p

v

p

v

H

P

H

H

L

NP

H

H

L

L

IncreasingPdecreasingHv

C= link speed (Mbps)

Hp= avg. hop distance (physical)

N= number of nodes


15/27


Problems/Limitations of Solution 1

Nonlinear objective functions.

Nonlinear constraints on wavelength continuity.

Resorted to heuristicsOptimal virtual topology design (Simulated Annealing)

Optimal packet routing on V.T. (Flow Deviation Algorithm)

No routing and wavelength assignment(Shortest-path lightpath routing; no constraints onwavelengths).


16/27


Highlights/Contributions of Solution 2

Complete Virtual Topology Design

Linear formulationOptimal solution

Objective: Minimize average hop distance

Assume: Wavelength conversion(Sparse conversion provides almost full conversion benefits).

Resource Budgeting Tradeoffs Important/Expensive Resources: Transceivers and

wavelengths

Dont under-utilize either of them!

Hardware cost model.

Optimal Reconfiguration Algorithm

Minimize reconfiguration time.


17/27


Optional Constraints / Simplifying Assumptions

Need scalability.

Physical topology is a subset of the virtual topology.

Bounded lightpath length

Prevent long convoluted lightpaths from occuring.

Prune the search spaceConsider Kshortest paths (bounded K).


18/27


Two Solutions from the LP

(a) Two-wavelengthsolution

(b) Five-wavelengthsolution


19/27


Hop Distance, Transceiver + Wavelength Utilization


20/27


Average Hop Distance


21/27


Transceiver Utilization


22/27


Wavelength Utilization


23/27


Heuristic Solutions


24/27


WDM Network Cost Model

2/log2111

m

N

m

mx

N

j

jN

i

im

i

i

i

it WC

W

R

W

TMCRTCC


25/27


Reconfiguration Algorithm

Generate linear formulations F(1)and F(2)corresponding to traffic

matrices sd1 and sd2.

Derive solutions and S(1)and S(2), corresponding to F(1)and F(2)

Modify F(2)to F(2)by adding the new constraint:

New objective function for F(2):

or

Although modis nonlinear, above reconfiguration formulation is linearsince the variables ps and Vs are binary.

2, ,

1

OPTji ds

sd

ij

sd sd

ij mn

ij

mn

ij

mn ppMinimize )1()2(:

ijijij VVMinimize )1()2(:


26/27


Reconfiguration Statistics


27/27

Optical NetworksBM-UC Davis148

Summary of Virtual Topology Design Principles

Use WDM to scale up an existing fiber-based WAN(Networks information carrying capacity increased

manifold)

Employ packet-switched virtual topology

imbedded on a physical topology as if we have a virtual Internet

(which is reconfigurable under user control) need optimum graph-imbedding algorithms

Reuse electronic switch of existing WAN as part of the WRS in the scaled-up WAN

light paths

Documents