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2OLD DOG
CONSULTING
Is the Sky Falling?
The only way to get your attention is to be alarmist
MPLS-TE is perfectly functional in today’s networks
But: MPLS-TE will not scale indefinitely The problem is the well-known “full mesh” or
“n-squared” problem The number of LSPs scales as the square of the
number of PEs
3OLD DOG
CONSULTING
What Do We Want to Achieve?
MPLS-TE is an important feature for many SPs Allow traffic to be groomed Optimize use of network resources Provide quality of service guaranties
Carriers look to provide edge-to-edge tunnels across their core networks Differentiated Services VPNs VLANS and pseudowires Multimedia content distribution Normal IP traffic
4OLD DOG
CONSULTING
What is the Scope of the Problem?
Consider a service provider network with 1000 PEs This is not outrageously large Such a network may be broken into areas or ASes
Consider a full mesh of PE-PE TE-LSPs Consider parallel tunnels for different services,
QoS levels, and for protection May give rise to multiples of 999,000 LSPs in the
core
What is the capacity of a core LSR? What is the capacity of a management system?
5OLD DOG
CONSULTING
What Are the Scaling Limits?
Management NMS
How many LSPs can the NMS process Management protocols
Reporting on large numbers of LSPs may overload the management network
LSR issues Memory capacity
Per LSP data requirements CPU capacity – largely an RSVP-TE protocol issue
Degradation of LSP setup times Soft state addressed by Refresh Reduction
MPLS forwarding plane Number of labels (Only 1048559 per interface)
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CONSULTING
The Snowflake Topology
Example network for analysis Meshed core of P nodes
Called P1 nodes Each Pi+1 node connected to
just one Pi node PE nodes connected to just one
Pn node Well-defined connectivity and
symmetry allows many important metrics to be computed
Number of levels & number of nodes per level may be varied We can vary the number of P1 nodes We can vary the ratio of Pi+1 to Pi We can vary the value n We can vary the number of PE nodes per Pn node
PE
P1
P2
7OLD DOG
CONSULTING
Analysing the Snowflake Topology
Define Pn a node at the nth level (level 1 is core) Sn the number of nodes at the nth level Mn the multiplier at the nth level (how many Pn+1 nodes are
connected to a Pn node) Ln number of LSPs seen by a Pn node
Discover LPE = 2*(SPE - 1) L2 = M2*(2*SPE - M2 - 1) L1 = M1*M2*(2*SPE – M2*(M1 + 1))
Practical numbers S1 = 10, M1 = 10, and M2 = 20 SPE = 2000 LPE = 3998 L2 = 79580 L1 = 756000
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CONSULTING
The Ladder Topology
Example network for analysis Core of P1 nodes looks
like a ladder Similar to many national
networks Symmetrical trees subtended
to core Each Pi+1 node connected to just one Pi node Each PE node connected to just one P node
Again: Well-defined connectivity and symmetry allows many
important metrics to be computed Number of levels & number of nodes per level may be varied
9OLD DOG
CONSULTING
Analysing the Ladder Topology
Same definitions as for snowflake network E the number of subtended edge nodes (PEs) to each
spar-node (E = M1*M2) Discover
LPE = 2*(SPE - 1) L2 = 2*M2*(SPE - 1) - M2*(M2 - 1) L1 ≈ E*E*S1*S1/2 + E*E*S1 + 3*E*E - E*M2
Practical numbers S 1 = 10, M1 = 10, and M2 = 20 E = 200 SPE = 2000 LPE = 3998 L2 = 79580 L1 = 2516000
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CONSULTING
Option 1 – Solve a Different Problem!
If a full mesh of PE-PE LSPs is too big, don’t build it! This is the bottom line if we don’t fix the problem
The suggestion is to build a full mesh of Pn-to-Pn LSPs, and perform routing or routing-based MPLS between Pn and PE
Scaling improves from O(10002)to O(1002)
But we lose functionality Why did we want a PE-PE mesh? How do we handle private address spaces? What if the traffic is not routable?
This may simply not be good enough to provide the function
11OLD DOG
CONSULTING
Option 2 – LSP Hierarchies
Well-known, core MPLS function Label stacks Forwarding Adjacencies (RFC 4206) Configured or automatic grooming
Possible to build a full or partialmesh of hierarchical tunnels
For example connect all P2 nodes Each P2 node must encapsulate each PE-PE LSP
in the correct tunnel Each P1 node only sees the P2-P2 tunnels
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CONSULTING
Scaling Properties of Hierarchies - Snowflake
Note that PE-PE tunnels don’t help P1-P1 tunnels are also no benefit (core is fully meshed) P2 nodes see all PE-PE LSPs and new tunnels
L2 = M2*(2*SPE - M2 - 1) + 2*(S2 - 1) Situation at P1 nodes is much better
L1 = M1*(2*S2 - M1 - 1) Numbers (S1 = 10, M1 = 10, and M2 = 20)
Flat 2-Level HierarchySPE 2000 2000LPE 3998 3998L2 79580 79778L1 756000 1890
Maybe insert another layer (P3 ) to increase the scaling? L3 remains high
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CONSULTING
Scaling Properties of Hierarchies - Ladder
Note that PE-PE tunnels don’t help But P1-P1 tunnels are good because core is not fully-
meshed L1 ≈ S1*S1/2 + 2*S1 + 2*E*E*(S1 - 1) - E*M2 - 2
Another level of hierarchy is also possible Add a mesh of P2-P2 tunnels
L1 = S1*S1/2 + 2*S1 + 2*M1*M1*S1 - M1(M1 + 1) – 2 L2 = 2*M2*(S(PE) - 1) - M2*(M2 - 1) + 2*(S(1)*M(1) - 1)
Numbers (S 1 = 10, M1 = 10, and M2 = 20)Flat 2-Level 3-Level
Hierarchy HierarchySPE 2000 2000 2000LPE 3998 3998 3998L2 79580 79580 79778L1 2516000 716060 1958
14OLD DOG
CONSULTING
Issues and Drawbacks for Hierarchies
Scaling is not good enough! Impact on layer adjacent to PEs is negligible
Actually impact is slightly negative Management burden
Plan and operate a secondary mesh Effectively the same burden as managing PEs or a
layered network Possible to consider auto-mesh techniques
Fast Reroute protection is a problem FRR struggles to protect tunnel end-points
Not obvious how to arrange the hierarchy when the network is not symmetrical E.g., some PEs closer to the core
15OLD DOG
CONSULTING
Option 3 – Multipoint-to-Point LSPs
LSPs merge automatically as they converge on the destination
Reduces the number of LSPs toward the egress Other LSP properties (e.g.,
bandwidth) must be cumulative TE is still possible, but
de-merge is not considered Should count “LSP state” not number of LSPs
New definition Xn the amount of LSP state
held at each Pn node For flat and hierarchical networks:
Each LSP adds one state at ingress or egress Each LSP adds two states at each transit node
16OLD DOG
CONSULTING
Scaling Properties of MP2P LSPs - Snowflake
XPE = 2*(SPE - 1)
X2 = SPE*(M2 + 1)
X1 = M1*M2*(S1 - 2) + SPE*(M1 + 1) Numbers (S1 = 10, M1 = 10, and M2 = 20)
Flat 2-Level Hierarchy P2MP
SPE 2000 2000 2000
XPE 3998 3998 3998
X2 159160 159358 42000
X1 1512000 3780 23600
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CONSULTING
Scaling Properties of MP2P LSPs - Ladder
XPE = 2*(SPE - 1)
X2 = (M2 + 1)*S1*E
X1 ≤ (4 + M1)*S1*E - M1*E Numbers (S1 = 10, M1 = 10, and M2 = 20)
Flat 2-Level 3-LevelP2MP
Hierarchy HierarchySPE 2000 2000 2000 2000
XPE 3998 3998 3998 3998
X2 159160 159160 159358 42000
X1 5032000 1433998 3898 26000
18OLD DOG
CONSULTING
Issues and Drawbacks for MP2P LSPs
Clear scaling benefits Better than flat networks Only thing that improves the situation adjacent to PEs
But… Data plane support
This will only ever be a packet/frame/cell technology Control plane support
RSVP does have MP2P support RSVP-TE features not yet specified or implemented
De-aggregation and disambiguation May be necessary to use label stack so that egress can
detect sender of data OAM may be more complex and require source labels New management applications needed FRR still to be designed
19OLD DOG
CONSULTING
Other Topics for Investigation
Cost-effectiveness of the network Revenue only generated by PEs K = S(PE)/(S(1)+S(2) + ... + S(n)) Many ways to improve scaling reduce cost-effectiveness
Fast Reroute What are the implications of FRR to scaling? Can scaling contributions be designed that can be protected
by FRR? Point-to-multipoint
What are the scaling properties of P2MP MPLS-TE? Domain boundaries (in particular AS boundaries)
Boundaries such as at area and AS borders cause constrictions
How can we reduce the number of LSPs seen by ABRs and ASBRs?
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CONSULTING
Conclusions, Next Steps, and References
MPLS-TE is not a scaling issue today But it won’t scale arbitrarily
We need to plan now for tomorrow’s scalability Hierarchical LSPs are not as good as expected MP2P LSPs may offer a better solution More research and implementation is needed
draft-ietf-mpls-te-scaling-analysis-01.txt Seisho Yaukawa (NTT) Adrian Farrel (Old Dog Consulting) Olufemi Komolafe (Cisco Systems)