Wavelength Band Switching in Multigranular Optical WDM Networks
Vishal Anand
Collaborators X. Cao, Dr. Y. Xiong and Dr. C. Qiao
LANDER, CSE Department, SUNY at Buffalo
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Vishal Anand
Outline
λ The Problem with present WDM networks
λ Concept of wavelength band switching: 3 layer waveband
switching OXC architecture
λ Wavelength Band Switching: Schemes and Grouping Strategies
λ Wavelength Band Switching Vs Wavelength Routed Networks:
How similar, How different
λ Performance of Wavelength Band Switching: Techniques for Static
and Dynamic Traffic: ILP, Algorithms and simulation results
λ A Single-layer waveband switching OXC architecture
λ Wavelength Vs Waveband Conversion
λ New techniques for failure recovery in WBS networks
λ Conclusions
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Present WDM networks : The Problem
λ Internet traffic demand on the rise
λ Only way to keep up: WDM
λ Causes deployment of more fibers and more
wavelengths per fiber (DWDM)
λ In-turn implies increased size of Optical Cross-connects
(OXC), with large port counts
λ Hence, managing/controlling (NMS, EMS) this large
amount of traffic, associated resources: critical,
difficult, complicated!
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Present WDM networks : The Problem
(cont'd)
λ This translates to increased cost: both Capital (CAPEX) and
Operating (OPEX)
λ Despite the technological advances:
λ in WDM, Photonic-XC systems, switching fabric
λ The deployment and potential use is limited
Unproven reliability and costs of huge switches (e.g.
1000x1000 ports)
λ Large footprint (size), power requirements and (un) scalability
concerns
λ
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The typical Optical
Cross-Connect (OXC)
λ Switching at an optical node—too many wavelength-ports
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Wavelength Band Switching
λ Wavelength band: a group of several wavelengths
λ WBS: A new switching hierarchy with multiple
granularity
λ WBS Networks: Use WBS in conjunction with a
multi-granular OXC, MG-OXC
Typical-OXC
A
λ
λ01
λ2
λ3
MG-OXC
Switch each wavelength individually
Total ports = 4 + 4x2 + 4x2 + 4 = 24+add/drop+mux/demux
D
B
C
Switch band of 4 wavelengths using 1 port
Total Ports = 1 + 1x2 + 1x2 + 1 = 6+add/drop+mux/demux only!
B
A
b0
C
b0
D
b0
b0
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A Three-layer MG-OXC
λ Any fiber (bands) can be
demultiplexed into bands
(wavelengths) using FTB/BTW
λ Any band (wavelength) can be
multiplexed into fibers (bands)
using BTF/WTB
λ Fibers/bands/wavelengths are
switched at the
FXC/BXC/WXC-layers
λ Port types
λ Cross-connect – bypass traffic
λ Add/drop – add/drop traffic
λ Mux/Demux – muxed/demuxed
traffic
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Example:WBS using a 3-layer MG-OXC
λ0
λ 2 individual lightpaths:
λ0 on fiber F1 bypassing
the node and λ1 to be
added locally
λ After demux. F1, λ0 is
extracted and grouped
with λ1 after going thro
muxer(s)
λ Finally λ0 and λ1 are
mux. (combined) in a
band and go out on
fiber F2 “together”
λ1
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Classification of WBS Schemes
λ
λ
λ
Use the pre-determined wavelength set scheme as it is the simplest
Each fiber has a fixed # of bands (B), each band has a fixed number of
wavelengths (W), which are consecutive (pre-determined)
Or : each fiber has a fixed # B, each band has a fixed # of wavelengths and these
wavelengths are chosen randomly (not necessarily consecutively) / adaptively
— may be more flexible, BUT too complex to realize in practice
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Waveband Grouping strategies
(1) end-to-end: grouping the lightpaths with the same
source-destination pair only;
(2) one-end:grouping the lightpaths from the same source
only OR grouping the lightpaths with same destination
only;
(3) sub-path: grouping the lightpaths with common
intermediate links (i.e. sub-paths); From any source to
any destination
λ Strategy (3) is the most general, BUT also complex
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WBS Vs classical Wavelength Routed
Networks (WRN)
λ Different objectives and techniques
λ WRN: typically minimize wavelengths or wavelength-hops(WH)
λ WBS networks: minimize the number of ports
λ Minimizing wavelengths does not minimize the num. of ports
λ Used an algorithm which optimizes (using Linear Prog.) the used
wavelengths by Routing & Wavelength Assignment (RWA), and
then does best effort grouping, backfired
λ Caused an increase rather than a decrease in port count
λ An ideal WBS algo. may need to trade a slight increase in
wavelengths for a much reduced port count
λ The WBS optimization problem has more constraints and harder
to solve
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WBS Vs WRN (cont'd)
λ Techniques developed for WRN, traffic grooming
cannot be applied directly to address WBS-problems
λ In WRN, traffic grooming is used to reduce (de) mux,
electronics, wavelengths and hence cost
λ WRN: any set of lower bit rate sub-wavelength traffic can be
multiplexed onto a wavelength
λ Only constraint is total bit rate ≤ max. bit rate of wavelength
λ E.g. any 12 SONET STS-1 (51.84 Mbps) signals can be
multiplexed onto a OC-12 wavelength, as:
12 x STS-1 = 622.08 Mbps = OC-12 (2.5Gbps)
λ WBS: at least one more constraint
λ Only the traffic carried by a fixed set (typically consecutive) can
be grouped into a band
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Performance of WBS networks: Static
case experimental Results
λ The problem:
λ Given:
λ Network topology, number of wavelengths per fiber (F), bands per
fiber (B) and granularity (W), network capacity is not fixed
λ A set of static traffic demands (i.e. lightpaths) – all given upfront
λ How to satisfy all the traffic using minimum number of ports, when no
wavelength conversion is available?
λ Approach:
1. Optimization using Integer linear Programming (ILP) model,
for details Refer [opticomm’02, Infocom’03]
λ Not feasible (uses too much time and memory) for large problem sizes
2.
Heuristic based approach for large problems
λ Based on waveband assignment strategy (3), sub-path grouping
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ILP formulation for WBS — central
ideas
λ Objective:
MIN [α ∑ WXC n + β ∑ BXC n + γ ∑ FXC n ] → 1(OR )
n
n
n
MIN ( max [α ∑ WXC n + β ∑ BXC n + γ ∑ FXC n ]) → 2
n
n
n
n
α = β = γ = 1 ⇒ all ports have equal cost
λ Minimize the total number of ports
λ Minimize the maximum size of a node (i.e. port count)
λ Variables
λ Node (i.e. ports therein) is the central point of interest
λ Define the property or characteristics of a node instead of a
link
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ILP formulation for WBS (cont'd)
λ Constraints
λ RWA: similar to traditional RWA ILP
λ Flow conservation
λ Wavelength capacity
λ Wavelength continuity
λ Waveband switching
λ Bypass lightpath uses exactly one of FXC/BXC/WXC crossconnect
λ Add lightpath uses exactly one add port at FXC/BXC/WXC
λ Drop lightpath uses exactly one drop port at FXC/BXC/WXC
λ Mux/demux
– Every added wavelength has to use a WTB mux (port)
– Every band has to use a BTF mux (port) before leaving node n
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ILP formulation for WBS (cont'd)
λ Port numbers at a node : calculated from the values of
the variables
λ WXC layer: sum of bypass/add/drop lightpaths
λ BXC layer: sum of ports for bypass/add/drop bands and ports
from WTB and BTW, mux/demux
λ FXC layer: sum of ports for bypass/add/drop fibers and ports
from FTB and BTF, mux/demux
λ RWA and grouping is done so that the ILP minimizes
the total number of ports above
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Heuristic Algorithms
λ WBO-RWA:Waveband Oblivious (but optimal) RWA
λ Use ILP formulations for traditional RWA that minimize the
total number of used wavelength-hop (WH)
λ Then group the assigned wavelengths into bands and calculate
the number of required ports
λ Best effort grouping, done as an afterthought, completely
oblivious to the existence of wavebands
λ BPHT: Balanced Path with Heavy-Traffic first waveband
assignment
λ Variations of BPHT, e.g. BTMH:balanced traffic with max-hop
first, BPMH:balanced path with max-hop first
λ Performance of BPHT the best
λ Hence show results of BPHT, WBO-RWA and ILP
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BPHT– central ideas
λ To maintain wavelength-continuity (no conversion),
assign longer paths, with more WHs first, to reduce
blocking
λ Assign bypass lightpaths (typically 60-80% of the traffic) first
λ Assign paths that have maximum links in common to
reduce ports by switching them together as a band
λ Stage 1: Load Balanced K shortest path (KSP) Routing
λ Start with the node-pair with max. WHs along its shortest path
λ Use k-shortest paths for every node-pair
λ Load balance by minimizing the maximum load on a link
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BPHT– central ideas (cont'd)
λ
Stage 2: Wavelength Assignment
λ
λ
λ
λ
λ
Consider all node-pair traffic with hops (hp ≥ 2) first
Define a set Qsd for every node pair (s,d), which includes all traffic whose
start/end are along the path from s to d
Calculate weight of each set Qsd,, Wsd = ∑ h p * Tp
p∈Q
Starting with the largest weight set, until all traffic is satisfied
1. Assign wavelengths to all traffic from same source ‘s’
2. Assign wavelengths to all traffic from same destination ‘d’
3. Recursively assign the remaining lightpaths in the set similarly
sd
Stage 3: Switching
λ
Once wavelengths are assigned, switch as many lightpaths using fibers,
the remaining as bands, and finally the still remaining individually at the
wavelength level
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Vishal Anand
Illustration of BPHT
State, after load
balanced routing
WS4D2 = ∑hp×tp =9
S4
S0
S1
S2
S3
2
1
D0
D1
3
4
6
5
LPs={1,2,3,4}
1
S4
S0
S1
2
LPs ={4,5,6}
D2
WS0D1 = ∑hp×tp =5x1+4x1+3x1+2x1=14
p∈PDS0
p∈PDS4
WS4D2 = ∑hp×tp =7
p∈PDS4
2
b0
S2
S3
b2
b1
D0
λ3
λ1
λ0
LPs={5,6}
D1
λ2
λ4
λ5
D2
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Performance Evaluation
λ
Define 3 Performance Metrics: each metric is a function
of the WBS algorithm ‘a’
1.
Total port number ratio T(a)
Total ( FXCn + BXCn + WXCn )u sin g WBS a lg orithm ' a '
Total (OXCn ) of ordinary − OXC
2.
Max port number ratio M(a)
Max( FXCn + BXCn + WXCn )u sin g WBS a lg orithm ' a '
Max(OXCn ) of ordinary − OXC
3.
Used wavelength channels ratio W(a)
λ − hop used by WBS a lg orithm ' a'
λ − hop used by optimal RWA without WBS
λ
λ
Improvement in port count is: 1-T(a)
By definition W(WBO-RWA) = 1
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Simulation Results I
λ Results of ILP model for a small network
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Simulation Results II
λ Results for a large network—Random traffic
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Simulation Results III
λ Results for a large network—Uniform traffic, W=4
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Performance of WBS networks:
Dynamic case experimental Results
λ
The problem:
λ Given:
λ
λ
Network topology, with fixed number of wavelengths per fiber (F), bands per
fiber (B) and granularity (W), now network capacity is fixed/limited
A set of dynamic incremental traffic demands (i.e. lightpaths): demands arrive
one after the other, with no knowledge of future demands
λ How to satisfy maximum traffic (i.e. with low blocking)
using minimum number of ports, when no wavelength
conversion is available?
λ
Approach:
1.
2.
Limited reconfiguration (to save ports) MG-OXC architecture
Heuristic MILB: Maximum Interference Length In Band
λ Based on assigning lightpaths routes & wavelengths in a band such that the
number of links shared with existing lightpaths in that band is maximized
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Dynamically reconfigured MG-OXC
λ To save on ports, do not allow
full reconfiguration
λ Instead of allowing any fiber/
band to be demuxed, allow
only a limited number of
bands to be demuxed
λ Num. bands in a fiber = Y,
allow only βY bands to be
demuxed into wavelengths,
β<1
λ Hence only limited
reconfigurability allowed
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MILB for Dynamic incremental traffic
λ Model the network as a band-graph with B layers – one
for each band
λ0
S1
S2
S0
S4
k0
S1
S2
S3
S7
S0
S4
S5
2 possible routes
S6
b0
S5
S3
S7
S6
Band layer -1
existing lightpaths
S1
k1
S2
S0
new lightpath
λ3
S4
λ2
S5
S3
b1
S7
S6
Band layer -2
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Performance Results: Dynamic Case
‰
λ MILB performs the best
λ Switches max. lightpaths as a group (band)
λ FF and RF only group as an afterthought,
For same number of ports RF, FF block
more lightpaths
λ β = 0.44, MILB achieves least blocking
with least port count
λ Blocking does not decrease with increase
in β, only due to lack of wavelengths, not
ports
λ Savings = (1- 0.44) ≅ 60%
λ Only at β = 1, FF has lower blocking, BUT
Compared MILB with First-Fit(FF)
at the expense of large port count !
and Random -fit (RF) for various
λ Suggests having/building-in 44% BTW
band sizes and β
ports, BUT not more
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Wavelength Hop Vs Num. Port
λ Trade-off : Wavelength Hop (WH) Vs Num. of Ports
λ While using ILP and heuristics for the Static Case and heuristics for
Dynamic Case
λ WHY?
λ Do not always use the shortest WH path
λ May use a longer WH path which increases used wavelength resources but
decrease ports
λ Static Case:
λ ILP: naturally chooses paths and wavelengths which minimizes ports, WH
minimization is secondary (a byproduct)
λ BPHT: a longer path may be used in step 1, for load balancing
λ Dynamic Case:
λ MILB: may choose a longer path and band which has more interference and
maximizes banding and port reduction, but this increases WH
λ Our techniques: perform WBS with only a small increase in
wavelength resources, with a large decrease in port count
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A Single-layer MG-OXC
λ Only certain “designated”
fibers (bands) can be
multiplexed or demultiplexed
λ For example, in the fig. only
fiber ‘n’ can be (de) multiplexed
into bands
λ only certain bands from this can
be (de) multiplexed into
wavelengths
λ Fibers 1,2 simply pass-thro,
switched at the FXC-layer
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Single Vs Multi-layer MG-OXC
Comparison criteria
Single Layer
Multi-layer
Num. Of Switches
Logical division: only 1
switch,fabric: better signal
quality
Physically 3 diff.
Layers/switches/fabrics
Num. Of Mux/DeMux
Eliminate FTB/BTW,
BTF/WTB (de) mux’s b/n
layers
FTB/BTW, BTF/WTB
(de)mux’s still needed
Control Complexity
Simpler architecture to
Relatively more complex
implement/configure/control
Num. Of ports
Ideally very few (fewer
than multi-layer)
Practically few
WBS algorithm
λVery Complex
λPractically impossible to
achieve port-count even
close to the ideal case
λResult in more blocking
for dynamic traffic
λRelatively simpler
λPossible to achieve a small
port-count with a simpler
algo. for both static and
dynamic traffic
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Wavelength and Waveband conversion
λ Waveband conversion is similar, but not identical to limited
wavelength conversion
λ With band conversion: converting b0 to b1, causes not only lambda-0
Ælambda-1, but also forces the conversion of lambda-1 Ælambda-3
simultaneously
λ In WRN, with full conversion, wavelength assignment is trivial
λ In WBS, conversion does facilitate grouping and ease wavelength requirement
λ But wavelength conversion does require a fiber/band to be first demultiplexed
into wavelengths Potentially increasing the port count
λ Waveband conversion allows conversion without this demultiplexing and
additional ports, but with the above constraints
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New techniques for failure recovery
λ New failures in WBS networks: port, mux/demux/bandconverters, causing wavelength and bands to fail
λ Thus, even if a link/fiber does not fail (as in WRN), the
above intra-fiber failures have to be accounted for
λ Use new Band-Merging and Band-Swapping methods
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Conclusions
λ Introduced the concept of Wavelength Band Switching (WBS)
λ Explored the advantage of WBS, and developed intelligent WBS
algorithms, optical cross-connect architectures
λ Developed ILP formulations and heuristics to consider the
efficient design of WBS optical networks for both Static and
Dynamic traffic
λ Intelligent WBS algorithms heuristics (such as BPHT, MILB) can
save considerably on port count. Bad heuristics such as WBORWA may need even more ports than ordinary-OXC network
λ There is a trade-off between wavelength-hop used and the total
port count in MG-OXC network
λ WBS to reduce ports requires only a small increase in wavelength
resources for a much larger decrease in port count (network cost)
λ Considered critical WBS issues such as conversion and failure
recovery
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