apoorv nayak prathyusha dasari traffic grooming. agenda improved approaches for cost effective...
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AgendaAgenda Improved approaches for cost effective traffic
grooming in WDM ring networks Motivation Terminology Single hop approach Multi hop approach
A Novel Generic Graph Model for Traffic Grooming in Heterogeneous WDM Mesh Networks
Motivation With WDM technology we can have dozens of
wavelengths on a fiber.
Increase in network capacity is accompanied with increase in the electronic multiplexing equipment.
Dominant cost is electronics and not fiber.
AimAim Goal is to minimize electronic costs by reducing
the number of ADM’s and make efficient use of wavelengths.
“Groom” a number of low rate traffic streams onto a higher rate stream and vice versa.
Reducing the number of wavelengths
SONET RingSONET Ring
Much of today’s physical layer infrastructure is built around SONET rings.
Constructed using fiber (one or two pairs usually used to provide protection) to connect SONET ADM’s.
ExampleExample
Signal from A split into two; one copy transmitted over the working ring (1) other copy over protection ring (8-7-6). B selects the best signal.
SONET ADMSONET ADM Add/Drop multiplexer.
Each ADM can multiplex multiple lower rate
streams to form a higher rate stream OR
demultiplex a higher rate stream to several
lower rate ones.
Employs O-E-O conversion.
Works at a particular wavelength.
WADMWADM Wavelength add/drop multiplexer. Emergence of WDM technology has enabled a single
fiber pair to support multiple wavelengths. Since ADM works on a single wavelength, if there are W
wavelengths, every node would need N*W ADM’s.
WADM contdWADM contdBut a node may not need to add / drop streams on
every wavelength.
WADM’s can add/drop only the wavelengths carrying
traffic to/ from a node.
AssumptionsAssumptions
Traffic demands are static and known a priori.
Traffic is uniform;total bandwidth required is
same for any s-d pair.
Unidirectional ring considered.
Single hop approachSingle hop approach
Uses the simulated annealing heuristic.
A node with a wavelength-k ADM can communicate
directly with all other nodes having wavelength-k ADM.
Formation of a wavelength-k logical ring which consists
of the subset of N nodes with a wavelength-k ADM.
Nodes within a logical ring communicate with each other
directly (single hop).
Example of single hop approachExample of single hop approachGiven data
Network layout Traffic demand matrix Number of available wavelengths : 2 Capacity of each wavelength : OC-3 Uniform traffic between any two nodes is OC-1.
Network TopologyNetwork Topology
0 1
3 2
0 1
23
fiber
t1
t2
t3
t4
t5 t6
a) Physical Network b) Traffic on the Network
Traffic Grooming Approach1 (Random)Traffic Grooming Approach1 (Random)
Total number of ADM’s needed = 8
Single hop traffic grooming algorithmSingle hop traffic grooming algorithm
do{do{
dcost = perturb();if(∆cost < 0 or (∆cost > 0 and exp(-∆cost/control) > rand
[0,1))) {
accept_change();chain++;
}else
reject_change();
} while(chain < ANN_CONST * G)
control = control * DEC_CONST;
} while(control > END)
TerminologyTerminology
Perturb() – Randomly swap positions of two circles in different
wavelengths.
ANN_CONST– Decides how long to run the algorithm before
system reaches equilibrium.
DEC_CONST - How fast to lower the control variable.
G – Grooming ratio (Ratio of the wavelength channel rate to the lowest traffic rate).
Multi hop approach (Hub based communication)Multi hop approach (Hub based communication)
Source and destination on different logical rings.
Solution OXC?
Still maturingCostly
Relatively inexpensive as compared to OXC More delay and reduced throughput Price-Performance tradeoff.
A “hub” node with an ADM for each wavelength. Multiple ADM’s at some nodes. Decide which nodes, how many ADM’s, which wavelengths.
Multiple ADM’s?
Approach followed in paper?
Example of a unidirectional multihop WDM ring networkExample of a unidirectional multihop WDM ring network
Terminology and assumptionsTerminology and assumptions W - Number of wavelengths.
Di - Number of ADM’s in the ith node.
G - Grooming ratio (Ratio of the wavelength channel
rate to the lowest traffic rate).
tij - Traffic requirement (Number of low rate circuits
between i and j for i-j pair).
tij = 1 for uniform traffic.
Given data
Number of nodes- NTraffic matrix- TGrooming ratio- G
ADM placement algorithmADM placement algorithm
Input N, G, t;Compute number of ADM’s needed at each node by the equation:
Compute number of wavelengths by the equation:
Create an ADM hub node;Place ADM’s needed at each node sequentially;
While (no of ADM’s and wavelengths can be reduced){
Assign traffic on each wavelength using shortest path;Traffic grooming (wavelength combining and segment swapping);
}
Wavelength CombiningWavelength CombiningIf capacity (i) < G and capacity (j) <GAnd capacity (i) + capacity (j) ≤ GThen the two wavelengths can be combined
2
3
4
W1 =1
W2 =2W1 =2
W2 =1
W1 =1
W2 =2
W1 =2
W2 =1
W1=3
W1=3 W1=3
W1=3
1
Segment SwappingSegment Swapping
Helps in wavelength combining by “manipulating” wavelengths such that all link capacities are less than G.
1
2
3
4
W1 = 2
W2 = 3
W3=1
W1 =3
W2 =2
W3=1
W1 =3
W2 =2
W3=1
W1 =2
W2 =3
W3=1
W1=3
W2=3
W1=3
W2=3 W1=3
W2=3
W1=3
W2=3
W1 =2
W2 =3
W3=1
W1 =2
W2 =3
W3=1
Example of multihop approachExample of multihop approach
Given data
N=5, node 0 is hub node
G = 3, tij = 1
By eqn 1, every node needs at least 2 ADMs
By eqn 2, total number of wavelengths is 8
A Novel generic ApproachA Novel generic Approach Objectives Generic Graph Model Auxiliary Graph
- Vertices
- Edges IGABAG Example Grooming Policies
- Comparison
In Heterogenenous NetworksIn Heterogenenous Networks
CSC 778 Fall 2007
Traffic Grooming :• Can be applied to static or dynamic traffic grooming problem.• Each node is characterized by various parameters - Optical switching/multiplexing capabilities- wavelength/waveband/fiber. - Electronic switching/multiplexing grooming capabilities. - Availability of wavelength conversion. - Number of transmitters/receivers.
CSC 778 Fall 2007
• Traffic grooming problem may have various objectives - Minimize cost (transmitters/receivers). - Minimize overall traffic load. - Minimize maximum traffic on any light path. - Minimize maximum wavelengths on any fiber.
ObjectivesObjectives
CSC 778 Fall 2007
• Construct auxiliary graph Add vertices and edges corresponding to network elements.
- Links- Wavelength converters- Electronic ports (transmitters/receivers)
Assign costs to links based on objective• Run shortest path algorithm
Generic Graph Model Generic Graph Model
CSC 778 Fall 2007
• Input and output vertex for each wavelength layer at each node• Input and output vertex for lightpath layer at each node• Input and output vertex for access layer at each node
Auxiliary Graph - VerticesAuxiliary Graph - Vertices
Auxiliary Graph - EdgesAuxiliary Graph - Edges
CSC 778 Fall 2007
• Wavelength Bypass Edges (WBE) - From each input to output port on a given wavelength layer. - Optical wavelength switching capability• Grooming Edges (GmE) - From input to output port on access layer if grooming is available. - Electronic switching capability.• Mux Edges (MuxE) - From output port on access layer to output port on lightpath layer.• Demux Edges (DmxE) - From input port on lightpath layer to output port on access layer.
Auxiliary Graph - EdgesAuxiliary Graph - Edges
CSC 778 Fall 2007
• Transmitter Edges (TxE) - From output port on access layer to output port on wavelength layer if transmitter is available .• Receiver Edges (RxE) - From input port on wavelength layer to input port on access layer if receiver is available.• Converter Edges (CvtE) - From input port on wavelength layer 1 to output port on wavelength layer 2 if optical wavelength conversion is available.
Auxiliary Graph - EdgesAuxiliary Graph - Edges
CSC 778 Fall 2007
• Wavelength-Link Edges (WLE) - From output port on wavelength layer l at node i to input port on wavelength layer l at node j if wavelength l is available on the physical link between i and j• Lightpath Edges (LPE) - From output port on the lightpath layer at node i to the input port of the lightpath layer at node j if there is a lightpath from node i to node j
Integrated Grooming Based on the Auxiliary Graph Integrated Grooming Based on the Auxiliary Graph (IGABAG)(IGABAG)
CSC 778 Fall 2007
• Traffic demand: T(s,d,g,m) - s : source, d : destination, g: granularity, m: amount of traffic in units of g• Step 1: Delete edges with capacity less than g.• Step 2: Find shortest path p from output port on the access layer of s to the input port on the access layer of d.• Step 3: If p contains wavelength-link edges, set up corresponding lightpaths.• Step 4: Route traffic demand along path p. If the capacity of lightpaths along p is less than m, route the maximum amount possible.• Step 5: Restore edges deleted in Step 1.• Step 6: Update graph G.
ExampleExample
CSC 778 Fall 2007
• Wavelength capacity: OC-48• Each node has 2 transmitters/receivers• Granularity: OC-12• Request 1: T(1, 0, OC-12, 2) -> Lightpath on 1 from N1 to N0• Request 2: T(2, 0, OC-12, 1)• Request 3: T(1, 0, OC-48, 1)
Example – Single-Hop GroomingExample – Single-Hop Grooming
CSC 778 Fall 2007
• Request 2: T(2, 0, OC-12, 1) - new lightpath on 2 from N2-N1-N0
• Request 3: T(1, 0, OC-48, 1)
Example – Multi-hop GroomingExample – Multi-hop Grooming
CSC 778 Fall 2007
• Request 2: T(2, 0, OC-12, 1) - new lightpath on 1 from N2-N1 - Existing lightpath on 1 from N1-N0• Request 3: T(1, 0, OC-48, 1)
Grooming OperationsGrooming Operations
CSC 778 Fall 2007
Add New Lightpath(s)
Single-hop or multi-hop grooming
Operation 1 No Single-hop
Operation 2 No Multi-hop
Operation 3 Yes Single-hop
Operation 4 Yes Multi-hop
Grooming PoliciesGrooming Policies
CSC 778 Fall 2007
• Minimize the Number of Traffic Hops (MinTH) - Attempt Operation 1 - Attempt Operation 3 - Between Operation 2 and 4, choose the one with fewest logical hops• Minimize the Number of Lightpaths (MinLP) - Attempt Operation 1 - Attempt Operation 2 - Attempt Operation 3 or 4• Minimize the Number of Wavelength-Links (MinWL) - Attempt Operation 1 - Attempt Operation 2 - Between Operation 3 and 4, choose the one with fewer wavelength links
Ordering of Requests for Static CaseOrdering of Requests for Static Case
CSC 778 Fall 2007
• Least Cost First (LCF) - Establish least-cost request first - Cost = (weight of shortest path for demand)/(amount of traffic)• Maximum Utilization First (MUF) - Select connection with maximum utilization first - Utilization = (amount of traffic)/(number of hops on physical topology)• Maximum Amount First (MAF) - Select connection with largest traffic demand first
Comparison of Policies – Non Blocking ModelComparison of Policies – Non Blocking Model
CSC 778 Fall 2007
AcknowledgmentsAcknowledgments• Improved Approaches for Cost-effective traffic grooming in WDM Ring Networks : Uniform-Traffic Case; Wonghong Cho, Jian Wang, Biswanath Mukherjee
• A Novel generic graph model for traffic grooming in heterogenous WDM mesh networks; Hongyue Zhu, Hui Zang, Biswanath Mukherjee
•Traffic grooming algorithms for reducing electronic multiplexing costs in WDM rings; Angela L. Chiu, Eytan H. Modiano
• An effective and comprehensive approach for traffic grooming and wavelength in SONET/WDM rings; Xijun Zhang, Chunming Qiao
•Improved approaches for cost-effective traffic grooming in WDM ring networks: Non-uniform traffic and bidirectional ring; Jian Wang, V. Rao Vemuri
•Connection Oriented Networks, Harry Perros