Network Working Group S. Yasukawa
Request for Comments: 5439 NTT
Category: Informational A. Farrel
Old Dog Consulting
O. Komolafe
Cisco Systems
February 2009
An Analysis of Scaling Issues in MPLSTE Core Networks
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Abstract
Traffic engineered Multiprotocol Label Switching (MPLSTE) is
deployed in providers' core networks. As providers plan to grow
these networks, they need to understand whether existing protocols
and implementations can support the network sizes that they are
planning.
This document presents an analysis of some of the scaling concerns
for the number of Label Switching Paths (LSPs) in MPLSTE core
networks, and examines the value of two techniques (LSP hierarchies
and multipointtopoint LSPs) for improving scaling. The intention
is to motivate the development of appropriate deployment techniques
and protocol extensions to enable the application of MPLSTE in large
networks.
This document only considers the question of achieving scalability
for the support of pointtopoint MPLSTE LSPs. Pointtomultipoint
MPLSTE LSPs are for future study.
Table of Contents
1. Introduction ....................................................3
1.1. Overview ...................................................3
1.2. Glossary of Notation .......................................5
2. Issues of Concern for Scaling ...................................5
2.1. LSP State ..................................................5
2.2. Processing Overhead ........................................6
2.3. RSVPTE Implications .......................................6
2.4. Management .................................................7
3. Network Topologies ..............................................8
3.1. The Snowflake Network Topology .............................9
3.2. The Ladder Network Topology ...............................11
3.3. Commercial Drivers for Selected Configurations ............14
3.4. Other Network Topologies ..................................15
4. Required Network Sizes .........................................16
4.1. Practical Numbers .........................................16
5. Scaling in Flat Networks .......................................16
5.1. Snowflake Networks ........................................17
5.2. Ladder Networks ...........................................18
6. Scaling Snowflake Networks with Forwarding Adjacencies .........22
6.1. TwoLayer Hierarchy .......................................22
6.1.1. Tuning the Network Topology to Suit the
TwoLayer Hierarchy ................................23
6.2. Alternative TwoLayer Hierarchy ...........................24
6.3. ThreeLayer Hierarchy .....................................25
6.4. Issues with Hierarchical LSPs .............................26
7. Scaling Ladder Networks with Forwarding Adjacencies ............27
7.1. TwoLayer Hierarchy .......................................27
7.2. ThreeLayer Hierarchy .....................................28
7.3. Issues with Hierarchical LSPs .............................29
8. Scaling Improvements through MultipointtoPoint LSPs ..........30
8.1. Overview of MP2P LSPs .....................................30
8.2. LSP State: A Better Measure of Scalability ................31
8.3. Scaling Improvements for Snowflake Networks ...............32
8.3.1. Comparison with Other Scenarios ....................33
8.4. Scaling Improvements for Ladder Networks ..................34
8.4.1. Comparison with Other Scenarios ....................36
8.4.2. LSP State Compared with LSP Numbers ................37
8.5. Issues with MP2P LSPs .....................................37
9. Combined Models ................................................39
10. An Alternate Solution .........................................39
10.1. Pros and Cons of the Alternate Solution ..................40
11. Management Considerations .....................................42
12. Security Considerations .......................................42
13. Recommendations ...............................................42
14. Acknowledgements ..............................................43
15. Normative References ..........................................43
16. Informative References ........................................43
1. Introduction
Network operators and service providers are examining scaling issues
as they look to deploy everlarger traffic engineered Multiprotocol
Label Switching (MPLSTE) networks. Concerns have been raised about
the number of Label Switched Paths (LSPs) that need to be supported
at the edge and at the core of the network. The impact on control
plane and management plane resources threatens to outweigh the
benefits and popularity of MPLSTE, while the physical limitations of
the routers may constrain the deployment options.
Historically, it has been assumed that all MPLSTE scaling issues can
be addressed using hierarchical LSP [RFC4206]. However, analysis
shows that the improvement gained by LSP hierarchies is not as
significant in all topologies and at all points in the network as
might have been presumed. Further, additional management issues are
introduced to determine the endpoints of the hierarchical LSPs and
to operate them. Although this does not invalidate the benefits of
LSP hierarchies, it does indicate that additional techniques may be
desirable in order to fully scale MPLSTE networks.
This document examines the scaling properties of two generic MPLSTE
network topologies and investigates the benefits of two scaling
techniques.
1.1. Overview
Physical topology scaling concerns are addressed by building networks
that are not fully meshed. Network topologies tend to be meshed in
the core but treeshaped at the edges, giving rise to a snowflake
design. Alternatively, the core may be more of a ladder shape with
treeshaped edges.
MPLSTE, however, establishes a logical full mesh between all edge
points in the network, and this is where the scaling problems arise
since the structure of the network tends to focus a large number of
LSPs within the core of the network.
This document presents two generic network topologies (the snowflake
and the ladder) and attempts to parameterize the networks by making
some generalities. It introduces terminology for the different
scaling parameters and examines how many LSPs might be required to be
carried within the core of a network.
Two techniques (hierarchical LSPs and multipointtopoint LSPs) are
introduced and an examination is made of the scaling benefits that
they offer as well as of some of the concerns with using these
techniques.
Of necessity, this document makes many generalizations. Not least
among these is a set of assumptions about the symmetry and
connectivity of the physical network. It is hoped that these
generalizations will not impinge on the usefulness of the overview of
the scaling properties that this document attempts to give. Indeed,
the symmetry of the example topologies tends to highlight the scaling
issues of the different solution models, and this may be useful in
exposing the worst case scenarios.
Although protection mechanisms like Fast Reroute (FRR) [RFC4090] are
briefly discussed, the main body of this document considers stable
network cases. It should be noted that makebeforebreak
reoptimisation after link failure may result in a significant number
of 'duplicate' LSPs. This issue is not addressed in this document.
It should also be understood that certain deployment models where
separate traffic engineered LSPs are used to provide different
services (such as layer 3 Virtual Private Networks (VPNs) [RFC4110]
or pseudowires [RFC3985]) or different classes of service [RFC3270]
may result in 'duplicate' or 'parallel' LSPs running between any pair
of provider edge nodes (PEs). This scaling factor is also not
considered in this document, but may be easily applied as a linear
factor by the reader.
The operation of security mechanisms in MPLSTE networks [MPLSSEC]
may have an impact on the ability of the network to scale. For
example, they may increase both the size and number of control plane
messages. Additionally, they may increase the processing overhead as
control plane messages are subject to processing algorithms (such as
encryption), and security keys need to be managed. Deployers will
need to consider the tradeoffs between scaling objectives and
security objectives in their networks, and should resist the
temptation to respond to a degradation of scaling performance by
turning off security techniques that have previously been deemed as
necessary. Further analysis of the effects of security measures on
scalability are not considered further in this document.
This document is designed to help service providers discover whether
existing protocols and implementations can support the network sizes
that they are planning. To do this, it presents an analysis of some
of the scaling concerns for MPLSTE core networks and examines the
value of two techniques for improving scaling. This should motivate
the development of appropriate deployment techniques and protocol
extensions to enable the application of MPLSTE in large networks.
This document only considers the question of achieving scalability
for the support of pointtopoint MPLSTE LSPs. Pointtomultipoint
MPLSTE LSPs are for future study.
1.2. Glossary of Notation
This document applies consistent notation to define various
parameters of the networks that are analyzed. These terms are
defined as they are introduced throughout the document, but are
grouped together here for quick reference. Refer to the full
definitions in the text for detailed explanations.
n A network level. n = 1 is the core of the network.
See Section 3 for more details on the definition of a level.
P(n) A node at level n in the network.
S(n) The number of nodes at level n. That is, the number of P(n)
nodes.
L(n) The number of LSPs seen by a P(n) node.
X(n) The number of LSP segment states held by a P(n) node.
M(n) The number of P(n+1) nodes subtended to a P(n) node.
R The number of rungs in a ladder network.
E The number of edge nodes (PEs) subtended below (directly or
indirectly) a sparnode in a ladder network.
K The costeffectiveness of the network expressed in terms of
the ratio of the number of PEs to the number of network nodes.
2. Issues of Concern for Scaling
This section presents some of the issues associated with the support
of LSPs at a Label Switching Router (LSR) or within the network.
These issues may mean that there is a limit to the number of LSPs
that can be supported.
2.1. LSP State
LSP state is the data (information) that must be stored at an LSR in
order to maintain an LSP. Here, we refer to the information that is
necessary to maintain forwarding plane state and the additional
information required when LSPs are established through control plane
protocols. While the size of the LSP state is implementation
dependent, it is clear that any implementation will require some data
in order to maintain LSP state.
Thus, LSP state becomes a scaling concern because as the number of
LSPs at an LSR increases, so the amount of memory required to
maintain the LSPs increases in direct proportion. Since the memory
capacity of an LSR is limited, there is a related limit placed on the
number LSPs that can be supported.
Note that techniques to reduce the memory requirements (such as data
compression) may serve to increase the number of LSPs that can be
supported, but this will only achieve a moderate multiplier and may
significantly decrease the ability to process the state rapidly.
In this document, we define X(n) as "the number of LSP segment states
held by a P(n) node." This definition observes that an LSR at the
end of an LSP only has to maintain state in one direction (i.e., into
the network), while a transit LSR must maintain state in both
directions (i.e., toward both ends of the LSP). Furthermore, in
multipointtopoint (MP2P) LSPs (see Section 8), a transit LSR may
need to maintain LSP state for one downstream segment (toward the
destination) and multiple upstream segments (from multiple sources).
That is, we define LSP segment state as the state necessary to
maintain an LSP in one direction to one adjacent node.
2.2. Processing Overhead
Depending largely on implementation issues, the number of LSPs
passing through an LSR may impact the processing speed for each LSP.
For example, control block search times can increase with the number
of control blocks to be searched, and even excellent implementations
cannot completely mitigate this fact. Thus, since CPU power is
constrained in any LSR, there may be a practical limit to the number
of LSPs that can be supported.
Further processing overhead considerations depend on issues specific
to the control plane protocols, and are discussed in the next
section.
2.3. RSVPTE Implications
Like many connectionoriented signaling protocols, RSVPTE (Resource
Reservation Protocol  Traffic Engineering) requires that state is
held within the network in order to maintain LSPs. The impact of
this is described in Section 2.1. Note that RSVPTE requires that
separate information is maintained for upstream and downstream
relationships, but does not require any specific implementation of
that state.
RSVPTE is a softstate protocol, which means that protocol messages
(refresh messages) must be regularly exchanged between signaling
neighbors in order to maintain the state for each LSP that runs
between the neighbors. A common period for the transmission (and
receipt) of refresh messages is 30 seconds, meaning that each LSR
must send and receive one message in each direction (upstream and
downstream) every 30 seconds for every LSP it supports. This has the
potential to be a significant constraint on the scaling of the
network, but various improvements [RFC2961] mean that this refresh
processing can be significantly reduced, allowing an implementation
to be optimized to remove nearly all concerns about softstate
scaling in a stable network.
Observations of existing implementations indicate that there may be a
threshold of around 50,000 LSPs above which an LSR struggles to
achieve sufficient processing to maintain LSP state. Although
refresh reduction [RFC2961] may substantially improve this situation,
it has also been observed that under these circumstances the size of
the Srefresh may become very large, and the processing required may
still cause significant disruption to an LSR.
Another approach is to increase the refresh time. There is a
correlation between the percentage increase in refresh time and the
improvement in performance for the LSR. However, it should be noted
that RSVPTE's softstate nature depends on regular refresh messages;
thus, a degree of functionality is lost by increasing the refresh
time. This loss may be partially mitigated by the use of the RSVPTE
Hello message, and can also be reduced by the use of various GMPLS
extensions [RFC3473], such as the use of [RFC2961] message
acknowledgements on all messages.
RSVPTE also requires that signaling adjacencies be maintained
through the use of Hello message exchanges. Although [RFC3209]
suggests that Hello messages should be retransmitted every 5 ms, in
practice, values of around 3 seconds are more common. Nevertheless,
the support of Hello messages can represent a scaling limitation on
an RSVPTE implementation since one message must be sent and received
to/from each signaling adjacency every time period. This can impose
limits on the number of neighbors (physical or logical) that an LSR
supports, but does not impact the number of LSPs that the LSR can
handle.
2.4. Management
Another practical concern for the scalability of large MPLSTE
networks is the ability to manage the network. This may be
constrained by the available tools, the practicality of managing
large numbers of LSPs, and the management protocols in use.
Management tools are software implementations. Although such
implementations should not constrain the control plane protocols, it
is realistic to appreciate that network deployments will be limited
by the scalability of the available tools. In practice, most
existing tools have a limit to the number of LSPs that they can
support. While a Network Management System (NMS) may be able to
support a large number of LSPs, the number that can be supported by
an Element Management System (EMS) (or the number supported by an NMS
perLSR) is more likely to be limited.
Similarly, practical constraints may be imposed by the operation of
management protocols. For example, an LSR may be swamped by
management protocol requests to read information about the LSPs that
it supports, and this might impact its ability to sustain those LSPs
in the control plane. OAM (Operations, Administration, and
Management), alarms, and notifications can further add to the burden
placed on an LSR and limit the number of LSPs it can support.
All of these considerations encourage a reduction in the number of
LSPs supported within the network and at any particular LSR.
3. Network Topologies
In order to provide some generic analysis of the potential scaling
issues for MPLSTE networks, this document explores two network
topology models. These topologies are selected partly because of
their symmetry, which makes them more tractable to a formulaic
approach, and partly because they represent generalizations of real
deployment models. Section 3.3 provides a discussion of the
commercial drivers for deployed topologies and gives more analysis of
why it is reasonable to consider these two topologies.
The first topology is the snowflake model. In this type of network,
only the very core of the network is meshed. The edges of the
network are formed as trees rooted in the core.
The second network topology considered is the ladder model. In this
type of network, the core of the network is shaped and meshed in the
form of a ladder and trees are attached rooted to the edge of the
ladder.
The sections that follow examine these topologies in detail in order
to parameterize them.
3.1. The Snowflake Network Topology
The snowflake topologies considered in this document are based on a
hierarchy of connectivity within the core network. PE nodes have
connectivity to Pnodes as shown in Figure 1. There is no direct
connectivity between the PEs. Dual homing of PEs to multiple Pnodes
is not considered in this document, although it may be a valuable
addition to a network configuration.
P
/\
/  \
/  \
/  \
PE PE PE
Figure 1 : PE to PNode Connectivity
The relationship between Pnodes is also structured in a hierarchical
way. Thus, as shown in Figure 2, multiple Pnodes at one level are
connected to a Pnode at a higher level. We number the levels such
that level 1 is the top level (top in our figure, and nearest to the
core of the network) and level (n) is immediately above level (n+1);
we denote a Pnode at level n as a P(n).
As with PEs, there is no direct connectivity between P(n+1) nodes.
Again, dual homing of P(n+1) nodes to multiple P(n) nodes is not
considered in this document, although it may be a valuable addition
to a network configuration.
P(n)
/\
/  \
/  \
/  \
P(n+1) P(n+1) P(n+1)
Figure 2 : Relationship between PNodes
At the top level, P(1) nodes are connected in a full mesh. In
reality, the level 1 part of the network may be slightly less well
connected than this, but assuming a full mesh provides for
generality. Thus, the snowflake topology comprises a clique with
topologically equivalent trees subtended from each node in the
clique.
The key multipliers for scalability are the number of P(1) nodes and
the multiplier relationship between P(n) and P(n+1) at each level,
down to and including PEs.
We define the multiplier M(n) as the number of P(n+1) nodes at level
(n+1) attached to any one P(n). Assume that M(n) is constant for all
nodes at level n. Since nodes at the same level are not
interconnected (except at the top level), and since each P(n+1) node
is connected to precisely one P(n) node, M(n) is one less than the
degree of the node at level n (that is, the P(n) node is attached to
M(n) nodes at level (n+1) and to 1 node at level (n1)).
We define S(n) as the number of nodes at level (n).
Thus:
S(n) = S(1)*M(1)*M(2)*...*M(n1)
So the number of PEs can be expressed as:
S(PE) = S(1)*M(1)*M(2)*...*M(n)
where the network has (n) layers of Pnodes.
Thus, we may depict an example snowflake network as shown in Figure
3. In this case:
S(1) = 3
M(1) = 3
S(2) = S(1)*M(1) = 9
M(2) = 2
S(PE) = S(1)*M(1)*M(2) = 18
PE PE PE PE PE PE
\ \/ \/ /
PEP(2) P(2) P(2) P(2)PE
\   /
\ /
PEP(2)P(1)P(1)P(2)PE
/ \ / \
PE \ / PE
\/
P(1)
/\
/  \
/  \
PEP(2) P(2) P(2)PE
/ /\ \
PE PE PE PE
Figure 3 : An Example Snowflake Network
3.2. The Ladder Network Topology
The ladder networks considered in this section are based on an
arrangement of routers in the core network that resembles a ladder.
Ladder networks typically have long and thin cores that are arranged
as conventional ladders. That is, they have one or more spars
connected by rungs. Each node on a spar may have:
 connection to one or more other spars,
 connection to a tree of other core nodes,
 connection to customer nodes.
Figure 4 shows a simplified example of a ladder network. A core of
twelve nodes makes up two spars connected by six rungs.
PE PE PE PE
PE PE PE  PE  PE PE PE  PE  PE
\ \/ /  \ \/
PEPPPPPPPE
     \
      PE
     
PEPPPPPP
/ /\ \ \ \ \
PE PE PE  PE  PE  PE  PE PE
PE PE PE PE
Figure 4 : A Simplified Ladder Network
In practice, not all nodes on a spar (call them sparnodes) need to
have subtended PEs. That is, they can exist simply to give
connectivity along the spar to other sparnodes, or across a rung to
another spar. Similarly, the connectivity between spars can be more
complex with multiple connections from one sparnode to another spar.
Lastly, the network may be complicated by the inclusion of more than
two spars (or simplified by reduction to a single spar).
These variables make the ladder network nontrivial to model. For
the sake of simplicity, we will make the following restrictions:
 There are precisely two spars in the core network.
 Every sparnode connects to precisely one sparnode on the other
spar. That is, each sparnode is attached to precisely one rung.
 Each sparnode connects to either one (endspar) or two (corespar)
other sparnodes on the same spar.
 Every sparnode has the same number of PEs subtended. This does
not mean that there are no Pnodes subtended to the sparnodes, but
does mean that the edge tree subtended to each sparnode is
identical.
From these restrictions, we are able to quantify a ladder network as
follows:
R  The number of rungs. That is, the number of sparnodes on
each spar.
S(1)  The number of sparnodes in the network. S(1)=2*R.
E  The number of subtended edge nodes (PEs) to each sparnode.
The number of rungs may vary considerably. A number less than 3 is
unlikely (since that would not be a significantly connected network),
and a number greater than 100 seems improbable (because that would
represent a very long, thin network).
E can be treated as for the snowflake network. That is, we can
consider a number of levels of attachment from P(1) nodes, which are
the sparnodes, through P(i) down to P(n), which are the PEs.
Practically, we need to only consider n=2 (PEs attached direct to the
sparnodes) and n=3 (one level of Pnodes between the PEs and the
sparnodes).
Let M(i) be the ratio of P(i) nodes to P(i1) nodes, i.e., the
connectivity between levels of Pnode as defined for the snowflake
topology. Hence, the number of nodes at any level (n) is:
S(n) = S(1)*M(1)*M(2)*...*M(n1)
So the number of PEs subtended to a sparnode is:
E = M(1)*M(2)*...*M(n)
And the number of PEs can be expressed as:
S(PE) = S(1)*M(1)*M(2)*...*M(n)
= S(1)*E
Thus, we may depict an example ladder network as shown in Figure 5.
In this case:
R = 5
S(1) = 10
M(1) = 2
S(2) = S(1)*M(1) = 20
M(2) = 2
E = M(1)*M(2) = 4
S(PE) = S(1)*E = 40
PE PE PE PE PE PE PE PE PE PE PE PE PE PE PE PE
\ \ \ \ / / / /
P(2) P(2) P(2) P(2) P(2) P(2) P(2) P(2)
\ \  \ /  / /
PE \ \  \ /  / / PE
\ \ \ \/ / / /
PEP(2)P(1)P(1)P(1)P(1)P(1)P(2)PE
    
    
    
PEP(2)P(1)P(1)P(1)P(1)P(1)P(2)PE
/ / /  /\ \ \ \
PE / /  / \  \ \ PE
/ /  / \  \ \
P(2) P(2) P(2) P(2) P(2) P(2) P(2) P(2)
/ / / / \ \ \ \
PE PE PE PE PE PE PE PE PE PE PE PE PE PE PE PE
Figure 5 : An Example Ladder Network
3.3. Commercial Drivers for Selected Configurations
It is reasonable to ask why these two particular network topologies
have been chosen.
The most important consideration is physical scalability. Each node
(Label Switching Router  LSR) is only able to support a limited
number of physical interfaces. This necessarily reduces the ability
to fully mesh a network and leads to the treelike structure of the
network toward the PEs.
A realistic commercial consideration for an operator is the fact that
the only revenuegenerating nodes in the network are the PEs. Other
nodes are needed only to support connectivity and scalability.
Therefore, there is a desire to maximize S(PE) while minimizing the
sum of S(n) for all values of (n). This could be achieved by
minimizing the number of levels and maximizing the connectivity at
each layer, M(n). Ultimately, however, this would produce a network
of just interconnected PEs, which is clearly in conflict with the
physical scaling situation.
Therefore, the solution calls for a "few" levels with "relatively
large" connectivity at each level. We might say that the cost
effectiveness of the network can be stated as:
K = S(PE)/(S(1)+S(2) + ... + S(n)) where n is the level above the PEs
We should observe, however, that this equation may be naive in that
the cost of a network is not actually a function of the number of
routers (since a router chassis is often free or low cost), but is
really a function of the cost of the line cards, which is, itself, a
product of the capacity of the line cards. Thus, the relatively high
connectivity decreases the costeffectiveness, while a topology that
tends to channel data through a network core tends to demand higher
capacity (and so, more expensive) line cards.
A further consideration is the availability of connectivity (usually
fibers) between LSR sites. Although it is always possible to lay new
fiber, this may not be costeffective or timely. The physical shape
and topography of the country in which the network is laid is likely
to be as much of a problem. If the country is 'long and thin', then
a ladder network is likely to be used.
This document examines the implications for control plane and data
plane scalability of this type of network when MPLSTE LSPs are used
to provide full connectivity between all PEs.
3.4. Other Network Topologies
As explained in Section 1, this document is using two symmetrical and
generalized network topologies for simplicity of modelling. In
practice, there are two other topological considerations.
a. Multihoming
It is relatively common for a node at level (n) to be attached to
more than one node at level (n1). This is particularly common at
PEs that may be connected to more than one P(n).
b. Meshing within a level
A level in the network will often include links between Pnodes at
the same level, including the possibility of links between PEs.
This may result in a network that looks like a series of
concentric circles with spokes.
Both of these features are likely to have some impact on the scaling
of the networks. However, for the purposes of establishing the
ground rules for scaling, this document restricts itself to the
consideration of the symmetrical networks described in Sections 2.1
and 2.2. Discussion of other network formats is for future study.
4. Required Network Sizes
An important question for this evaluation and analysis is the size of
the network that operators require. How many PEs are required? What
ratio of P to PE is acceptable? How many ports do devices have for
physical connectivity? What type of MPLSTE connectivity between PEs
is required?
Although presentation of figures for desired network sizes must be
treated with caution because history shows that networks grow beyond
all projections, it is useful to set some acceptable lower bounds.
That is, we can state that we are interested in networks of at least
a certain size.
The most important features are:
 The network should have at least 1000 PEs.
 Each pair of PEs should be connected by at least one LSP in each
direction.
4.1. Practical Numbers
In practice, reasonable target numbers are as follows.
S(PE) >= 1000
Number of levels is 3. That is: 1, 2, and PE.
M(2) <= 20
M(1) <= 20
S(1) <= 100
5. Scaling in Flat Networks
Before proceeding to examine potential scaling improvements, we need
to examine how well the flat networks described in the previous
sections scale.
Consider the requirement for a full mesh of LSPs linking all PEs.
That is, each PE has an LSP to and from every other LSP. Thus, if
there are S(PE) PEs in the network, there are S(PE)*(S(PE)  1) LSPs.
Define L(n) as the number of LSPs handled by a level (n) LSR.
L(PE) = 2*(S(PE)  1)
5.1. Snowflake Networks
There are a total of S(PE) PEs in the network and, since each PE
establishes an LSP with every other PE, it would be expected that
there are S(PE)  1 LSPs incoming to each PE and the same number of
LSPs outgoing from the same PE, giving a total of 2(S(PE)  1) on the
incident link. Hence, in a snowflake topology (see Figure 3), since
there are M(2) PEs attached to each P(2) node, it may tempting to
think that L(2) (the number of LSPs traversing each P(2) node) is
simply 2*(S(PE)  1)*M(2). However, it should be noted that of the
S(PE)  1 LSPs incoming to each PE, M(2)  1 originated from nodes
attached to the same P(2) node, and so this value would count the
LSPs between the M(2) PEs attached to each P(2) node twice: once when
outgoing from the M(2)  1 other nodes and once when incoming into a
particular PE.
There are a total of M(2)*(M(2)  1) LSPs between these M(2) PEs and,
since this value is erroneously included twice in 2*(S(PE)  1)*M(2),
the correct value is:
L(2) = 2*M(2)*(S(PE)  1)  M(2)*(M(2)  1)
= M(2)*(2*S(PE)  M(2)  1)
An alternative way of looking at this, that proves extensible for the
calculation of L(1), is to observe that each PE subtended to a P(2)
node has an LSP in each direction to all S(PE)  M(2) PEs in the rest
of the system, and there are M(2) such locally subtended PEs; thus,
2*M(2)*(S(PE)  M(2)). Additionally, there are M(2)*(M(2)  1) LSPs
between the locally subtended PEs. So:
L(2) = 2*M(2)*(S(PE)  M(2)) + M(2)*(M(2)  1)
= M(2)*(2*S(PE)  M(2)  1)
L(1) can be computed in the same way as this second evaluation of
L(2). Each PE subtended below a P(1) node has an LSP in each
direction to all PEs not below the P(1) node. There are M(1)*M(2)
PEs below the P(1) node, so this accounts for 2*M(1)*M(2)*(S(PE) 
M(1)*M(2)) LSPs. To this, we need to add the number of LSPs that
pass through the P(1) node and that run between the PEs subtended
below the P(1). Consider each P(2): it has M(2) PEs, each of which
has an LSP going to all of the PEs subtended to the other P(2) nodes
subtended to the P(1). There are M(1)  1 such other P(2) nodes, and
so M(2)*(M(1)  1) other such PEs. So the number of LSPs from the
PEs below a P(2) node is M(2)*M(2)*(M(1)  1). And there are M(1)
P(2) nodes below the P(1), giving rise to a total of
M(2)*M(2)*M(1)*(M(1)  1) LSPs. Thus:
L(1) = 2*M(1)*M(2)*(S(PE)  M(1)*M(2)) + M(2)*M(2)*M(1)*(M(1)  1)
= M(1)*M(2)*(2*S(PE)  M(2)*(M(1) + 1))
So, for example, with S(1) = 5, M(1) = 10, and M(2) = 20, we see:
S(PE) = 1000
L(PE) = 1998
L(2) = 39580
L(1) = 356000
Alternatively, with S(1) = 10, M(1) = 10, and M(2) = 20, we see:
S(PE) = 2000
L(PE) = 3998
L(2) = 79580
L(1) = 756000
In both examples, the number of LSPs at the core (P(1)) nodes is
probably unacceptably large, even though there are only a relatively
modest number of PEs. In fact, L(2) may even be too large in the
second example.
5.2. Ladder Networks
In ladder networks, L(PE) remains the same at 2*(S(PE)  1).
L(2) can be computed using the same mechanism as for the snowflake
topology because the subtended tree is the same format. Hence,
L(2) = 2*M(2)*(S(PE)  1)  M(2)*(M(2)  1)
But L(1) requires a different computation because each P(1) not only
sees LSPs for the subtended PEs, but is also a transit node for some
of the LSPs that cross the core (the core is not fully meshed).
Each P(1) sees:
o all of the LSPs between locally attached PEs,
o less those LSPs between locally attached PEs that can be served
exclusively by the attached P(2) nodes,
o all LSPs between locally attached PEs and remote PEs, and
o LSPs in transit that pass through the P(1).
The first three numbers are easily determined and match what we have
seen from the snowflake network. They are:
o E*(E1)
o M(1)*M(2)*(M(2)1) = E*(M(2)  1)
o 2*E*E*(S(1)  1)
The number of LSPs in transit is more complicated to compute. It is
simplified by not considering the ends of the ladders but by
examining an arbitrary segment of the middle of the ladder, such as
shown in Figure 6. We look to compute and generalize the number of
LSPs traversing each core link (labeled a and b in Figure 6) and so
determine the number of transit LSPs seen by each P(1).
: : : : : :
: : : : : :
P(2) P(2) P(2) P(2) P(2) P(2)
\  \ /  /
\  \ /  /
\ \/ /
......P(1)P(1)P(1)......
 a  
 b 
  
......P(1)P(1)P(1)......
/ /\ \
/  / \  \
/  / \  \
P(2) P(2) P(2) P(2) P(2) P(2)
: : : : : :
: : : : : :
Figure 6 : An Arbitrary Section of a Ladder Network
Of course, the number of LSPs carried on links a and b in Figure 6
depends on how LSPs are routed through the core network. But if we
assume a symmetrical routing policy and an even distribution of LSPs
across all shortest paths, the result is the same.
Now we can see that each P(1) sees half of 2a+b LSPs (since each LSP
would otherwise be counted twice as it passed through the P(1)),
except that some of the LSPs are locally terminated and so are only
included once in the sum 2a+b.
So L(1) = a + b/2 
(locally terminated transit LSPs)/2 +
(locally contained LSPs)
Thus:
L(1) = a + b/2 
2*E*E*(S(1)  1)/2 +
E*(E1)  E*(M(2)  1)
= a + b/2 +
E*E*(2  S(1))  E*M(2)
So all we have to do is work out a and b.
Recall that the ladder length R = S(1)/2, and define X = E*E.
Consider the contribution made by all of the LSPs that make n hops on
the ladder to the totals of each of a and b. If the ladder was
unbounded, then we could say that in the case of a, there are n*2X
LSPs along the spar only, and n(n1)*2X/n = 2X(n1) LSPs use a rung
and the spar. Thus, the LSPs that make n hops on the ladder
contribute (4n2)X LSPs to a. Note that the edge cases are special
because LSPs that make only one hop on the ladder cannot transit a
P(1) but only start or end there.
So with a ladder of length R = S(1)/2, we could say:
R
a = SUM[(4i2)*X] + 2RX
i=2
= 2*X*R*(R+1)
And similarly, considering b in an unbounded ladder, the LSPs that
only travel one hop on the LSP are a special case, contributing 2X
LSPs, and every other LSP that traverses n hops on the ladder
contributes 2n*2X/n = 4X LSPs. So:
R+1
b = 2X + SUM[4X]
i=2
= 2*X + 4*X*R
In fact, the ladders are bounded, and so the number of LSPs is
reduced because of the effect of the ends of the ladders. The links
that see the most LSPs are in the middle of the ladder. Consider a
ladder of length R; a node in the middle of the ladder is R/2 hops
away from the end of the ladder. So we see that the formula for the
contribution to the count of sparonly LSPs for a is only valid up to
n=R/2, and for sparandrung LSPs, up to n=1+R/2. Above these
limits, the contribution made by sparonly LSPs decays as (nR/2)*2X.
However, for a firstorder approximation, we will use the values of a
and b as computed above. This gives us an upper bound of the number
of LSPs without using a more complex formula for the reduction made
by the effect of the ends of the ladder.
From this:
L(1) = a + b/2 +
E*E*(2  S(1))  E*M(2)
= 2*X*R*(R+1) +
X + 2*X*R +
E*E*(2  S(1))  E*M(2)
= E*E*S(1)*(1 + S(1)/2) +
E*E + E*E*S(1) +
2*E+E  E*E*S(1)  E*M(2)
= E*E*S(1)*(1 + S(1)/2) + 3*E+E  E*M(2)
= E*E*S(1)*S(1)/2 + E*E*S(1) + 3*E*E  E*M(2)
So, for example, with S(1) = 6, M(1) = 10, and M(2) = 17, we see:
E = 170
S(PE) = 1020
L(PE) = 2038
L(2) = 34374
L(1) = 777410
Alternatively, with S(1) = 10, M(1) = 10, and M(2) = 20, we see:
E = 200
S(PE) = 2000
L(PE) = 3998
L(2) = 79580
L(1) = 2516000
In both examples, the number of LSPs at the core (P(1)) nodes is
probably unacceptably large, even though there are only a relatively
modest number of PEs. In fact, L(2) may even be too large in the
second example.
Compare the L(1) values with the total number of LSPs in the system
S(PE)*(S(PE)  1), which is 1039380 and 3998000, respectively.
6. Scaling Snowflake Networks with Forwarding Adjacencies
One of the purposes of LSP hierarchies [RFC4206] is to improve the
scaling properties of MPLSTE networks. LSP tunnels (sometimes known
as Forwarding Adjacencies (FAs)) may be established to provide
connectivity over the core of the network, and multiple edgetoedge
LSPs may be tunneled down a single FA LSP.
In our network we consider a mesh of FA LSPs between all core nodes
at the same level. We consider two possibilities here. In the
first, all P(2) nodes are connected to all other P(2) nodes by LSP
tunnels, and the PEtoPE LSPs are tunneled across the core of the
network. In the second, an extra layer of LSP hierarchy is
introduced by connecting all P(1) nodes in an LSP mesh and tunneling
the P(2)toP(2) tunnels through these.
6.1. TwoLayer Hierarchy
In this hierarchy model, the P(2) nodes are connected by a mesh of
tunnels. This means that the P(1) nodes do not see the PEtoPE
LSPs.
It remains the case that:
L(PE) = 2*(S(PE)  1)
L(2) is slightly increased. It can be computed as the sum of all
LSPs for all attached PEs, including the LSPs between the attached PE
(this figure is unchanged from Section 5.1, i.e., M(2)*(2*S(PE) 
M(2)  1)), plus the number of FA LSPs providing a mesh to the other
P(2) nodes. Since the number of P(2) nodes is S(2), each P(2) node
sees 2*(S(2)  1) FA LSPs. Thus:
L(2) = M(2)*(2*S(PE)  M(2)  1) + 2*(S(2)  1)
L(1), however, is significantly reduced and can be computed as the
sum of the number of FA LSPs to and from each attached P(2) to each
other P(2) in the network, including (but counting only once) the FA
LSPs between attached P(2) nodes. In fact, the problem is identical
to the L(2) computation in Section 5.1. So:
L(1) = M(1)*(2*S(2)  M(1)  1)
So, for example, with S(1) = 5, M(1) = 10, and M(2) = 20, we see:
S(PE) = 1000
S(2) = 50
L(PE) = 1998
L(2) = 39678
L(1) = 890
Alternatively, with S(1) = 10, M(1) = 10, and M(2) = 20, we see:
S(PE) = 2000
S(2) = 100
L(PE) = 3998
L(2) = 79778
L(1) = 1890
So, in both examples, potential problems at the core (P(1)) nodes
caused by an excessive number of LSPs can be avoided, but any problem
with L(2) is made slightly worse, as can be seen from the table
below.
Example Count  Unmodified  2Layer
  (Section 5.1)  Hierarchy
+++
A  L(2)  39580  39678
 L(1)  356000  890
+++
B  L(2)  79580  79778
 L(1)  756000  1890
6.1.1. Tuning the Network Topology to Suit the TwoLayer Hierarchy
Clearly, we can reduce L(2) by selecting appropriate values of S(1),
M(1), and M(2). We can do this without negative consequences, since
no change will affect L(PE) and since a large percentage increase in
L(1) is sustainable now that L(1) is so small.
Observe that:
L(2) = M(2)*(2*S(PE)  M(2)  1) + 2*(S(2)  1)
where S(PE) = S(1)*M(1)*M(2) and S(2) = S(1)*M(1). So L(2) scales
with M(2)^2 and we can have the most impact by reducing M(2) while
keeping S(PE) constant.
For example, with S(1) = 10, M(1) = 10, and M(2) = 10, we see:
S(PE) = 1000
S(2) = 100
L(PE) = 1998
L(2) = 20088
L(1) = 1890
And similarly, with S(1) = 20, M(1) = 20, and M(2) = 5, we see:
S(PE) = 2000
S(2) = 400
L(PE) = 3998
L(2) = 20768
L(1) = 15580
These considerable scaling benefits must be offset against the cost
effectiveness of the network. Recall from Section 3.3 that:
K = S(PE)/(S(1)+S(2) ... + S(n))
where n is the level above the PEs, so that for our network:
K = S(PE) / (S(1) + S(2))
Thus, in the first example the costeffectiveness has been halved
from 1000/55 to 1000/110. In the second example, it has been reduced
to roughly one quarter, changing from 2000/110 to 2000/420.
So, although the tuning changes may be necessary to reach the desired
network size, they come at a considerable cost to the operator.
6.2. Alternative TwoLayer Hierarchy
An alternative to the twolayer hierarchy presented in Section 6.1 is
to provide a full mesh of FA LSPs between P(1) nodes. This technique
is only of benefit to any nodes in the core of the level 1 network.
It makes no difference to the PE and P(2) nodes since they continue
to see only the PEtoPE LSPs. Furthermore, this approach increases
the burden at the P(1) nodes since they have to support all of the
PEtoPE LSPs as in the flat model plus the additional 2*(S(1)  1)
P(1)toP(1) FA LSPs. Thus, this approach should only be considered
where there is a mesh of Pnodes within the ring of P(1) nodes, and
is not considered further in this document.
6.3. ThreeLayer Hierarchy
As demonstrated by Section 6.2, introducing a mesh of FA LSPs at the
top level (P(1)) has no benefit, but if we introduce an additional
level in the network (P(3) between P(2) and PE) to make a fourlevel
snowflake, we can introduce a new layer of FA LSPs so that we have a
full mesh of FA LSPs between all P(3) nodes to carry the PEtoPE
LSPs, and a full mesh of FA LSPs between all P(2) nodes to carry the
P(3)toP(3) LSPs.
The number of PEs is S(PE) = S(1)*M(1)*M(2)*M(3), and the number of
PEtoPE LSPs at a PE remains L(PE) = 2*(S(PE)  1).
The number of LSPs at a P(3) can be deduced from Section 6.1. It is
the sum of all LSPs for all attached PEs, including the LSPs between
the attached PE, plus the number of FA LSPs providing a mesh to the
other P(3) nodes.
L(3) = M(3)*(2*S(PE)  M(3)  1) + 2*(S(3)  1)
The number of LSPs at P(2) can also be deduced from Section 6.1 since
it is the sum of all LSPs for all attached P(3) nodes, including the
LSPs between the attached PE plus the number of FA LSPs providing a
mesh to the other P(2) nodes.
L(2) = M(2)*(2*S(3)  M(2)  1) + 2*(S(2)  1)
Finally, L(1) can be copied straight from 6.1.
L(1) = M(1)*(2*S(2)  M(1)  1)
For example, with S(1) = 5, M(1) = 5, M(2) = 5, and M(3) = 8, we see:
S(PE) = 1000
S(3) = 125
S(2) = 25
L(PE) = 1998
L(3) = 16176
L(2) = 1268
L(1) = 220
Similarly, with S(1) = 5, M(1) = 5, M(2) = 8, and M(3) = 10, we see:
S(PE) = 2000
S(3) = 200
S(2) = 25
L(PE) = 3998
L(3) = 40038
L(2) = 3184
L(1) = 220
Clearly, there are considerable scaling improvements with this three
layer hierarchy, and all of the numbers (even L(3) in the second
example) are manageable.
Of course, the extra level in the network tends to reduce the cost
effectiveness of the networks with values of K = 1000/155 and K =
2000/230 (from 1000/55 and 2000/110) for the examples above. That is
a reduction by a factor of 3 in the first case and 2 in the second
case. Such a change in costeffectiveness has to be weighed against
the desire to deploy such a large network. If LSP hierarchies are
the only scaling tool available, and networks this size are required,
the costeffectiveness may need to be sacrificed.
6.4. Issues with Hierarchical LSPs
A basic observation for hierarchical scaling techniques is that it is
hard to have any impact on the number of LSPs that must be supported
by the level of P(n) nodes adjacent to the PEs (for example, it is
hard to reduce L(3) in Section 6.3). In fact, the only way we can
change the number of LSPs supported by these nodes is to change the
scaling ratio M(n) in the network  in other words, to change the
number of PEs subtended to any P(n). But such a change has a direct
effect on the number of PEs in the network and so the cost
effectiveness is impacted.
Another concern with the hierarchical approach is that it must be
configured and managed. This may not seem like a large burden, but
it must be recalled that the P(n) nodes are not at the edge of the
network  they are a set of nodes that must be identified so that
the FA LSPs can be configured and provisioned. Effectively, the
operator must plan and construct a layered network with a ring of
P(n) nodes giving access to the level (n) network. This design
activity is open to considerable risk as failing to close the ring
(i.e., allowing a node to be at both level (n+1) and at level (n))
may cause operational confusion.
Protocol techniques (such as IGP automesh [RFC4972]) have been
developed to reduce the configuration necessary to build this type of
multilevel network. In the case of automesh, the routing protocol
is used to advertise the membership of a 'mesh group', and all
members of the mesh group can discover each other and connect with
LSP tunnels. Thus, the P(n) nodes giving access to level (n) can
advertise their existence to each other, and it is not necessary to
configure each with information about all of the others. Although
this process can help to reduce the configuration overhead, it does
not eliminate it, as each member of the mesh group must still be
planned and configured for membership.
An important consideration for the use of hierarchical LSPs is how
they can be protected using MPLS Fast Reroute (FRR) [RFC4090]. FRR
may provide link protection either by protecting the tunnels as they
traverse a broken link or by treating each level (n) tunnel LSP as a
link in level (n+1) and providing protection for the level (n+1) LSPs
(although in this model, fault detection and propagation time may be
an issue). Node protection may be performed in a similar way, but
protection of the first and last nodes of a hierarchical LSP is
particularly difficult. Additionally, the whole notion of scaling
with regard to FRR gives rise to separate concerns that are outside
the scope of this document as currently formulated.
Finally, observe that we have been explaining these techniques using
conveniently symmetrical networks. Consider how we would arrange the
hierarchical LSPs in a network where some PEs are connected closer to
the center of the network than others.
7. Scaling Ladder Networks with Forwarding Adjacencies
7.1. TwoLayer Hierarchy
In Section 6.2, we observed that there is no value to placing FA LSPs
between the P(1) nodes of our example snowflake topologies. This is
because those LSPs would be just one hop long and would, in fact,
only serve to increase the burden at the P(1) nodes. However, in the
ladder model, there is value to this approach. The P(1) nodes are
the sparnodes of the ladder, and they are not all mutually adjacent.
That is, the P(1)toP(1) hierarchical LSPs can create a full mesh of
P(1) nodes where one does not exist in the physical topology.
The number of LSPs seen by a P(1) node is then:
o all of the tunnels terminating at the P(1) node,
o any transit tunnels, and
o all of the LSPs due to subtended PEs.
This is a substantial reduction; all of the transit LSPs are reduced
to just one per remote P(1) that causes any transit LSP. So:
L(1) = 2*(S(1)  1) +
O(S(1)*S(1)/2) +
2*E*E*(S(1)  1) + E*(E1)  E*(M(2)  1)
where O(S(1)*S(1)/2) gives an upper bound order of magnitude. So:
L(1) = S(1)*S(1)/2 + 2*S(1) + 2*E*E*(S(1)  1)  E*M(2)  2
So, in our two examples:
With S(1) = 6, M(1) = 10, and M(2) = 17, we see:
E = 170
S(PE) = 1020
L(PE) = 2038
L(2) = 34374
L(1) = 286138
Alternatively, with S(1) = 10, M(1) = 10, and M(2) = 20, we see:
E = 200
S(PE) = 2000
L(PE) = 3998
L(2) = 79580
L(1) = 716060
Both of these show significant improvements over the previous L(1)
figures of 777410 and 2516000. But the numbers are still too large
to manage, and there is no improvement in the L(2) figures.
7.2. ThreeLayer Hierarchy
We can also apply the threelayer hierarchy to the ladder model. In
this case, the number of LSPs between P(1) nodes is not reduced, but
tunnels are also set up between all P(2) nodes. Thus, the number of
LSPs seen by a P(1) node is:
o all of the tunnels terminating at the P(1) node,
o any transit tunnels between P(1) nodes, and
o all of the LSPs due to subtended P(2) nodes.
No PEtoPE LSPs are seen at the P(1) nodes.
L(1) = 2*(S(1)  1) +
O(S(1)*S(1)/2) +
2*(S(1)  1)*M(1)*M(1) + M(1)*(M(1)  1)
where O(S(1)*S(1)/2) gives an upper bound order of magnitude. So:
L(1) = S(1)*S(1)/2 + 2*S(1) + 2*M(1)*M(1)*S(1)  M(1)(M(1) + 1)  2
Unfortunately, there is a small increase in the number of LSPs seen
by the P(2) nodes. Each P(2) now sees all of the PEtoPE LSPs that
it saw before and is also an endpoint for a set of P(2)toP(2)
tunnels. Thus, L(2) increases to:
L(2) = 2*M(2)*(S(PE)  1)  M(2)*(M(2)  1) + 2*(S(1)*M(1)  1)
So, in our two examples:
With S(1) = 6, M(1) = 10, and M(2) = 17, we see:
E = 170
S(PE) = 1020
L(PE) = 2038
L(2) = 34492
L(1) = 1118
Alternatively, with S(1) = 10, M(1) = 10, and M(2) = 20, we see:
E = 200
S(PE) = 2000
L(PE) = 3998
L(2) = 79778
L(1) = 1958
This represents a very dramatic decrease in LSPs across the core.
7.3. Issues with Hierarchical LSPs
The same issues exist for hierarchical LSPs as described in Section
6.4. Although dramatic improvements can be made to the scaling
numbers for the number of LSPs at core nodes, this can only be done
at the cost of configuring P(2) to P(2) tunnels. The mesh of P(1)
tunnels is not enough.
But the sheer number of P(2) to P(2) tunnels that must be configured
is a significant management burden that can only be eased by using a
technique like automesh [RFC4972].
It is significant, however, that the scaling problem at the P(2)
nodes cannot be improved by using tunnels and that the only solution
to ease this in the hierarchical approach would be to institute
another layer of hierarchy (that is, P(3) nodes) between the P(2)
nodes and the PEs. This is, of course, a significant expense.
8. Scaling Improvements through MultipointtoPoint LSPs
An alternative (or complementary) scaling technique has been proposed
using multipointtopoint (MP2P) LSPs. The fundamental improvement
in this case is achieved by reducing the number of LSPs toward the
destination as LSPs toward the same destination are merged.
This section presents an overview of MP2P LSPs and describes their
applicability and scaling benefits.
8.1. Overview of MP2P LSPs
Note that the MP2P LSPs discussed here are for MPLSTE and are not
the same concept familiar in the Label Distribution Protocol (LDP)
described in [RFC5036].
Traffic flows generally converge toward their destination and this
can be utilized by MPLS in constructing an MP2P LSP. With such an
LSP, the Label Forwarding Information Base (LFIB) mappings at each
LSR are manytoone so that multiple pairs {incoming interface,
incoming label} are mapped to a single pair {outgoing interface,
outgoing label}. Obviously, if perplatform labels are used, this
mapping may be optimized within an implementation.
It is important to note that with MP2P MPLSTE LSPs, the traffic
flows are merged. That is, some additional form of identifier is
required if demerging is required. For example, if the payload is
IP traffic belonging to the same client network, no additional de
merging information is required since the IP packet contains
sufficient data. On the other hand, if the data comes, for example,
from a variety of VPN client networks, then the flows will need to be
labeled in their own right as pointtopoint (P2P) flows, so that
traffic can be disambiguated at the egress of the MP2P LSPs.
Techniques for establishing MP2P MPLSTE LSPs and for assigning the
correct bandwidth downstream of LSP merge points are out of the scope
of this document.
8.2. LSP State: A Better Measure of Scalability
Consider the network topology shown in Figure 3. Suppose that we
establish MP2P LSP tunnels such that there is one tunnel terminating
at each PE, and that that tunnel has every other PE as an ingress.
Thus, a PEtoPE MP2P LSP tunnel would have S(PE)1 ingresses and one
egress, and there would be S(PE) such tunnels.
Note that there still remain 2*(S(PE)  1) PEtoPE P2P LSPs that are
carried through these tunnels.
Let's consider the number of LSPs handled at each node in the
network.
The PEs continue to handle the same number of PEtoPE P2P LSPs, and
must also handle the MP2P LSPs. So:
L(PE) = 2*(S(PE)  1) + S(PE)
But all P(n) nodes in the network only handle the MP2P LSP tunnels.
Nominally, this means that L(n) = S(PE) for all values of n. This
would appear to be a great success with the number of LSPs cut to
completely manageable levels.
However, the number of LSPs is not the only issue (although it may
have some impact for some of the scaling concerns listed in Section
4). We are more interested in the amount of LSP state that is
maintained by an LSR. This reflects the amount of storage required
at the LSR, the amount of protocol processing, and the amount of
information that needs to be managed.
In fact, we were also interested in this measure of scalability in
the earlier sections of this document, but in those cases we could
see a direct correlation between the number of LSPs and the amount of
LSP state since transit LSPs had two pieces of state information (one
on the incoming and one on the outgoing interface), and ingress or
egress LSPs had just one piece of state.
We can quantify the amount of LSP state according to the number of
LSP segments managed by an LSR. So (as above), in the case of a P2P
LSP, an ingress or egress has one segment to maintain, while a
transit has two segments. Similarly, for an MP2P LSP, an LSR must
maintain one set of state information for each upstream segment
(which, we can assume, is in a onetoone relationship with the
number of upstream neighbors) and exactly one downstream segment 
ingresses obviously have no upstream neighbors, and egresses have no
downstream segments.
So we can start again on our examination of the scaling properties of
MP2P LSPs using X(n) to represent the amount of LSP state held at
each P(n) node.
8.3. Scaling Improvements for Snowflake Networks
At the PEs, there is only connectivity to one other network node: the
P(2) node. But note that if P2P LSPs need to be used to allow
disambiguation of data at the MP2P LSP egresses, then these P2P LSPs
are tunneled within the MP2P LSPs. So X(PE) is:
X(PE) = 2*(S(PE)  1) if no disambiguation is required,
and
X(PE) = 4*(S(PE)  1) if disambiguation is required.
Each P(2) node has M(2) downstream PEs. The P(2) sees a single MP2P
LSP targeted at each downstream PE with one downstream segment (to
that PE) and M(2)  1 upstream segments from the other subtended PEs.
Additionally, each of these LSPs has an upstream segment from the one
upstream P(1). This gives a total of M(2)*(1 + M(2)) LSP segments.
There are also LSPs running from the subtended PEs to every other PE
in the network. There are S(PE)  M(2) such PEs, and the P(2) sees
one upstream segment for each of these from each subtended PE. It
also has one downstream segment for each of these LSPs. This gives
(M(2) + 1)*(S(PE)  M(2)) LSP segments.
Thus:
X(2) = M(2)*(1 + M(2)) + (M(2) + 1)*(S(PE)  M(2))
= S(PE)*(M(2) + 1)
Similarly, at each P(1) node there are M(1) downstream P(2) nodes and
so a total of M(1)*M(2) downstream PEs. Each P(1) is connected in a
full mesh with the other P(1) nodes and so has (S(1)  1) neighbors.
The P(1) sees a single MP2P LSP targeted at each downstream PE. This
has one downstream segment (to the P(2) to which the PE is connected)
and M(1)  1 upstream segments from the other subtended P(2) nodes.
Additionally, each of these LSPs has an upstream segment from each of
the P(1) neighbors. This gives a total number of LSP segments of
M(1)*M(2)*(M(1) + S(1)  1).
There are also LSPs running from each of the subtended PEs to every
other PE in the network. There are S(PE)  M(1)M(2) such PEs, and
the P(1) sees one upstream segment for each of these from each
subtended P(2) (since the aggregation from the subtended PEs has
already happened at the P(2) nodes). It also has one downstream
segment to the appropriate next hop P(1) neighbor for each of these
LSPs. This gives (M(1) + 1)*(S(PE)  M(1)*M(2)) LSP segments.
Thus:
X(1) = M(1)*M(2)*(M(1) + S(1)  1) +
(M(1) + 1)*(S(PE)  M(1)*M(2))
= M(1)*M(2)*(S(1)  2) + S(PE)*(M(1) + 1)
So, for example, with S(1) = 10, M(1) = 10, and M(2) = 10, we see:
S(PE) = 1000
S(2) = 100
X(PE) = 3996 (or 1998)
X(2) = 11000
X(1) = 11800
And similarly, with S(1) = 20, M(1) = 20, and M(2) = 5, we see:
S(PE) = 2000
S(2) = 400
X(PE) = 5996 (or 2998)
X(2) = 12000
X(1) = 39800
8.3.1. Comparison with Other Scenarios
For comparison with the examples in Sections 5 and 6, we need to
convert those LSPbased figures to our new measure of LSP state.
Observe that each LSP in Sections 5 and 6 generates two state units
at a transit LSR and one at an ingress or egress. So we can provide
conversions as follows:
Section 5 (flat snowflake network)
L(PE) = 2*(S(PE)  1)
L(2) = M(2)*(2*S(PE)  M(2)  1)
L(1) = M(1)*M(2)*(2*S(PE)  M(2)*(M(1) + 1))
X(PE) = 2*(S(PE)  1)
X(2) = 2*M(2)*(2*S(PE)  M(2)  1)
X(1) = 2*M(1)*M(2)*(2*S(PE)  M(2)*(M(1) + 1))
For the example with S(1) = 10, M(1) = 10, and M(2) = 10, this
gives a comparison table as follows:
Count  Unmodified  MP2P
++
X(PE)  1998  3996
X(2)  39780  11000
X(1)  378000  11800
Clearly, this technique is a significant improvement over the flat
network within the core of the network, although the PEs are more
heavily stressed if disambiguation is required.
Section 6.1 (twolayer hierarchy snowflake network)
L(PE) = 2*(S(PE)  1)
L(2) = M(2)*(2*S(PE)  M(2)  1) + 2*(S(2)  1)
L(1) = M(1)*(2*S(2)  M(1)  1)
X(PE) = 2*(S(PE)  1)
X(2) = 2*M(2)*(2*S(PE)  M(2)  1) + 2*(S(2)  1)
X(1) = 2*M(1)*(2*S(2)  M(1)  1)
Note that in the computation of X(2) the hierarchical LSPs only add
one state at each P(2) node.
For the same example with S(1) = 10, M(1) = 10, and M(2) = 10, this
gives a comparison table as follows:
Count  2Layer  MP2P
 Hierarchy 
++
X(PE)  1998  3996
X(2)  39978  11000
X(1)  3780  11800
We can observe that the MP2P model is better at P(2), but the
hierarchical model is better at P(1).
In fact, this comparison can be generalized to observe that the MP2P
model produces its best effects toward the edge of the network, while
the hierarchical model makes most impression at the core. However,
the requirement for disambiguation of P2P LSPs tunneled within the
MP2P LSPs does cause a double burden at the PEs.
8.4. Scaling Improvements for Ladder Networks
MP2P LSPs applied just within the ladder will not make a significant
difference, but applying MP2P for all LSPs and at all nodes makes a
very big difference without requiring any further configuration.
LSP state at a sparnode may be divided into those LSPs' segments
that enter or leave the sparnode due to subtended PEs (local LSP
segments), and those that enter or leave the sparnode due to remote
PEs (remote segments).
The local segments may be counted as:
o E LSPs targeting local PEs
o (S(1)1)*E*M(1) LSPs targeting remote PEs
The remote segments may be counted as:
o (S(1)1)*E outgoing LSPs targeting remote PEs
o <= 3*S(1)*E incoming LSPs targeting any PE (there are precisely
P(1) nodes attached to any other P(1) node)
Hence, using X(1) as a measure of LSP state rather than a count of
LSPs, we get:
X(1) <= E + (S(1)1)*E*M(1) + (S(1)1)*E + 3*S(1)*E
<= (4 + M(1))*S(1)*E  M(1)*E
The number of LSPs at the P(2) nodes is also improved. We may also
count the LSP state in the same way so that there are:
o M(2) LSPs targeting local PEs,
o M(2)*(S(1)*E) LSPs from local PEs to all other PEs, and
o S(1)*E  M(2) LSPs to remote PEs.
So using X(2) as a measure of LSP state and not a count of LSPs, we
have:
X(2) = M(2) + M(2)*(S(1)*E) + S(1)*E  M(2)
= (M(2) + 1)*S(1)*E
Our examples from Section 5.2 give us the following numbers:
With S(1) = 6, M(1) = 10, and M(2) = 17, we see:
E = 170
S(PE) = 1020
X(PE) = 2038
X(2) = 18360
X(1) <= 12580
Alternatively, with S(1) = 10, M(1) = 10, and M(2) = 20, we see:
E = 200
S(PE) = 2000
X(PE) = 3998
X(2) = 42000
X(1) <= 26000
8.4.1. Comparison with Other Scenarios
The use of MP2P compares very favorably with all scaling scenarios.
It is the only technique able to reduce the value of X(2), and it
does this by a factor of almost two. The impact on X(1) is better
than everything except the threelevel hierarchy.
The following table provides a quick crossreference for the figures
for the example ladder networks. Note that the previous figures are
modified to provide counts of LSP state rather than LSP numbers.
Again, each LSP contributes one state at its end points and two
states at transit nodes.
Thus, for the all cases we have:
X(PE) = 2*(S(PE)  1) or
X(PE) = 4*(S(PE)  1) if disambiguation is required.
In the unmodified (flat) case, we have:
X(2) = 2*(M(2)*(2*S(PE)  M(2)  1))
X(1) = 2*(M(1)*M(2)*(2*S(PE)  M(2)*(M(1) + 1)))
In the twolevel hierarchy, we have:
X(2) = 2*(2*M(2)*(S(PE)  1)  M(2)*(M(2)  1))
X(1) = S(1)*S(1) + 2*S(1) + 4*E*E*(S(1)  1)  2*E*M(2)  2
In the threelevel hierarchy, we have:
X(2) = 2*(2*M(2)*(S(PE)  1)  M(2)*(M(2)  1)) + 2*(S(1)*M(1)  1)
X(1) = S(1)*S(1) + 2*S(1) + 4*M(1)*M(1)*S(1)  2*M(1)(M(1) + 1)  2
Example A: S(1) = 6, M(1) = 10, and M(2) = 17
Example B: S(1) = 10, M(1) = 10, and M(2) = 20
Example Count  Unmodified  2Level  3Level  MP2P
   Hierarchy  Hierarchy 
+++++
A  X(2)  68748  68748  68866  18360
 X(1)  1554820  572266  2226  12580
+++++
B  X(2)  159160  159160  159358  42000
 X(1)  5032000  1433998  3898  26000
8.4.2. LSP State Compared with LSP Numbers
Recall that in Section 8.3, the true benefit of MP2P was analyzed
with respect to the LSP segment state required, rather than the
actual number of LSPs. This proved to be a more accurate comparison
of the techniques because the MP2P LSPs require state on each branch
of the LSP, so the saving is not linear with the reduced number of
LSPs.
A similar analysis could be performed here for the ladder network.
The net effect is that it increases the state by an order of two for
all transit LSPs in the P2P models, and by a multiplier equal to the
degree of a node in the MP2P model.
A rough estimate shows that, as with snowflake networks, MP2P
provides better scaling than the onelevel hierarchical model and is
considerably better at the core. But MP2P compares less will with
the twolevel hierarchy especially in the core.
8.5. Issues with MP2P LSPs
The biggest challenges for MP2P LSPs are the provision of support in
the control and data planes. To some extent, support must also be
provided in the management plane.
Control plane support is just a matter of defining the protocols and
procedures [MP2PRSVP], although it must be clearly understood that
this will introduce some complexity to the control plane.
Hardware issues may be a little more tricky. For example, the
capacity of the upstream segments must never (allowing for
statistical oversubscription) exceed the capacity of the downstream
segment. Similarly, data planes must be equipped with sufficient
buffers to handle incoming packet collisions.
The management plane will be impacted in several ways. Firstly, the
management applications will need to handle LSPs with multiple
senders. This means that, although the applications need to process
fewer LSPs, they will be more complicated and will, in fact, need to
process the same number of ingresses and egresses. Other issues like
diagnostics and OAM would also need to be enhanced to support MP2P,
but might be borrowed heavily from LDP networks.
Lastly, note that when the MP2P solution is used, the receiver (the
single egress PE of an MP2P tunnel) cannot use the incoming label as
an indicator of the source of the data. Contrast this with P2P LSPs.
Depending on deployment, this might not be an issue since the PEPE
connectivity may in any case be a tunnel with inner labels to
discriminate the data flows.
In other deployments, it may be considered necessary to include
additional PEPE P2P LSPs and tunnel these through the MP2P LSPs.
This would require the PEs to support twice as many LSPs. Since PEs
are not usually as fully specified as Prouters, this may cause some
concern; however, the use of penultimate hop popping on the MP2P LSPs
might help to reduce this issue.
In all cases, care must be taken not to confuse the reduction in the
number of LSPs with a reduction in the LSP state that is required.
In fact, the discussion in Section 8.3 is slightly optimistic since
LSP state toward the destination will probably need to include sender
information and so will increase depending on the number of senders
for the MP2P LSP. Section 8.4, on the other hand, counts LSP state
rather than LSPs. This issue is clearly dependent on the protocol
solution for MP2P RSVPTE, which is out of scope for this document.
MPLS Fast Reroute (FRR) [RFC4090] is an attractive scheme for
providing rapid local protection from node or link failures. Such a
scheme has, however, not been designed for MP2P at the time of
writing, so it remains to be seen how practical it could be,
especially in the case of the failure of a merge node. Initial
examination of this case suggests that FRR would not be a problem for
MP2P, given that each flow can be handled separately.
As a final note, observe that the MP2P scenario presented in this
document may be optimistic. MP2P LSP merging may be hard to achieve
between LSPs with significantly different traffic and Quality of
Service (QoS) parameters. Therefore, it may be necessary to increase
the number of MP2P LSPs arriving at an egress.
9. Combined Models
There is nothing to prevent the combination of hierarchical and MP2P
solutions within a network.
Note that if MP2P LSPs are tunneled through P2P FA LSPs across the
core, none of the benefit of LSP merging is seen for the hops during
which the MP2P LSPs are tunneled.
On the other hand, it is possible to construct solutions where MP2P
FA LSPs are constructed within the network, resulting in savings from
both modes of operation.
10. An Alternate Solution
A simple solution to reducing the number of LSP tunnels handled by
any node in the network has been proposed. In this solution it is
observed that part of the problem is caused purely by the total
number of LSP in the network, and that this is a function of the
number of PEs since a full mesh of PEPE LSPs is required. The
conclusion of this observation is to move the tunnel endpoints
further into the network so that, instead of having a full mesh of
PEPE tunnels, we have only a full mesh of P(n)P(n) tunnels.
Obviously, there is no change in the physical network topology, so
the PEs remain subtended to the P(n) nodes, and the consequence is
that there is no TE on the links between PEs and P(n) nodes.
In this case, we have already done the hard work for computing the
number of LSPs in the previous sections. The power of the analysis
in the earlier sections is demonstrated by its applicability to this
new model  all we need to do is make minor changes to the formulae.
This is most simply done by removing a layer from the network. We
introduce the term "tunnel endpoint" (TEP) and replace the P(n)
nodes with TEPs. Thus, the example of a flat snowflake network in
Figure 3 becomes as shown in Figure 7. Corresponding changes can be
made to all of the sample topologies.
PE PE PE PE PE PE
\ \/ \/ /
PETEP TEP TEP TEPPE
\   /
\ /
PETEPP(1)P(1)TEPPE
/ \ / \
PE \ / PE
\/
P(1)
/\
/  \
/  \
PETEP TEP TEPPE
/ /\ \
PE PE PE PE
Figure 7 : An Example Snowflake Network with Tunnel EndPoints
To perform the scaling calculations we need only replace the PE
counts in the formulae with TEP counts, and observe that there is one
fewer layer in the network. For example, in the flat snowflake
network shown in Figure 7, we can see that the number of LSPs seen at
a TEP is:
L(TEP) = 2*(S(TPE)  1)
In our sample networks, S(TPE) is typically of the order of 50 or 100
(the original values of S(2)), so L(TEP) is less than 200, which is
quite manageable.
Similarly, the number of LSPs handled by a P(1) node can be derived
from the original formula for the number of LSPs seen at a P(2) node,
since all we have done is reduce n in P(n) from 2 to 1. So our new
formula is:
L(1) = M(1)*(2*S(TEP)  M(1)  1)
With figures for M(1) = 10 and S(TEP) = 100, this gives us L(1) =
1890. This is also very manageable.
10.1. Pros and Cons of the Alternate Solution
On the face of it, this alternate solution seems very attractive.
Simply by contracting the edges of the tunnels into the network, we
have shown a dramatic reduction in the number of tunnels needed, and
there is no requirement to apply any additional scaling techniques.
But what of the PEP(n) links? In the earlier sections of this
document, we have assumed that there was some requirement for PEPE
LSPs with TE properties that extended to the PEP(n) links at both
ends of each LSP. That means that there was a requirement to provide
reservationbased QoS on those links, to be able to discriminate
traffic flows for prioritybased treatment, and to be able to
distinguish applications and sources that send data based on the LSPs
that carry the data.
It might be argued that, since the PEP(n) links do not offer any
routing options (each such link provides the only access to the
network for a PE), most of the benefits of tunnels are lost on these
peripheral links. However, TE is not just about routing. Just as
important are the abilities to make resource reservations, to
prioritize traffic, and to discriminate between traffic from
different applications, customers, or VPNs.
Furthermore, in multihoming scenarios where each PE is connected to
more than one P(n) or where a PE has multiple links to a single P(n),
there may be a desire to preselect the link to be used and to direct
the traffic to that link using a PEPE LSP. Note that multihoming
has not been considered in this document.
Operationally, P(n)P(n) LSPs offer the additional management
overhead that is seen for hierarchical LSPs described in Section 6.
That is, the LSPs have to be configured and established through
additional configuration or management operations that are not
carried out at the PEs. As described in Section 6, automesh
[RFC4972] could be used to ease this task. But it must be noted
that, as mentioned above, some of the key uses of tunnels require
that traffic is classified and placed in an appropriate tunnel
according to its traffic class, endpoints, originating application,
and customer (such as client VPN). This information may not be
readily available for each packet at the P(n) nodes since it is PE
based information. Of course, it is possible to conceive of
techniques to make this information available, such as assigning a
different label for each class of traffic, but this gives rise to the
original problem of larger numbers of LSPs.
Our conclusion is, therefore, that this alternate technique may be
suitable for the general distribution of traffic based solely on the
destination, or on a combination of the destination and key fields
carried in the IP header. In this case, it can provide a very
satisfactory answer to the scaling issues in an MPLSTE network. But
if more sophisticated packet classification and discrimination is
required, this technique will make the desired function hard to
achieve, and the tradeoff between scaling and featurelevel will
swing too far towards solving the scaling issue at the expense of
delivery of function to the customer.
11. Management Considerations
The management issues of the models presented in this document have
been discussed inline. No one solution is without its management
overhead.
Note, however, that scalability of management tools is one of the
motivators for this work and that network scaling solutions that
reduce the active management of LSPs at the cost of additional effort
to manage the more static elements of the network represent a
benefit. That is, it is worth the additional effort to set up MP2P
or FA LSPs if it means that the network can be scaled to a larger
size without being constrained by the management tools.
The MP2P technique may prove harder to debug through OAM methods than
the FA LSP approach.
12. Security Considerations
The techniques described in this document use existing or yettobe
defined signaling protocol extensions and are subject to the security
provided by those extensions. Note that we are talking about
tunneling techniques used within the network and that both approaches
are vulnerable to the creation of bogus tunnels that deliver data to
an egress or consume network resources.
The fact that the MP2P technique may prove harder to debug through
OAM methods than the FA LSP approach is a security concern since it
is important to be able to detect misconnections.
General issues of the relationship between scaling and security are
covered in Section 1.1, but the details are beyond the scope of this
document. Readers are referred to [MPLSSEC] for details of MPLS
security techniques.
13. Recommendations
The analysis in this document suggests that the ability to signal
MP2P MPLSTE LSPs is a desirable addition to the operator's MPLSTE
toolkit.
At this stage, no further recommendations are made, but it would be
valuable to consult more widely to discover:
 The concerns of other service providers with respect to network
scalability.
 More opinions on the realistic constraints to the network
parameters listed in Section 4.
 Desirable values for the costeffectiveness of the network
(parameter K).
 The applicability, manageability, and support for the two
techniques described.
 The feasibility of combining the two techniques, as discussed in
Section 9.
 The level of concern over the loss of functionality that would
occur if the alternate solution described in Section 10 was
adopted.
14. Acknowledgements
The authors are grateful to JeanLouis Le Roux for discussions and
review input. Thanks to Ben NivenJenkins, JP Vasseur, Loa
Andersson, Anders Gavler, Ben Campbell, and Tim Polk for their
comments. Thanks to Dave Allen for useful discussion of the math.
15. Normative References
[RFC4206] Kompella, K. and Y. Rekhter, "Label Switched Paths (LSP)
Hierarchy with Generalized MultiProtocol Label Switching
(GMPLS) Traffic Engineering (TE)", RFC 4206, October
2005.
16. Informative References
[RFC2961] Berger, L., Gan, D., Swallow, G., Pan, P., Tommasi, F.,
and S. Molendini, "RSVP Refresh Overhead Reduction
Extensions", RFC 2961, April 2001.
[RFC3209] Awduche, D., Berger, L., Gan, D., Li, T., Srinivasan, V.,
and G. Swallow, "RSVPTE: Extensions to RSVP for LSP
Tunnels", RFC 3209, December 2001.
[RFC3270] Le Faucheur, F., Wu, L., Davie, B., Davari, S., Vaananen,
P., Krishnan, R., Cheval, P., and J. Heinanen, "Multi
Protocol Label Switching (MPLS) Support of Differentiated
Services", RFC 3270, May 2002.
[RFC3473] Berger, L., Ed., "Generalized MultiProtocol Label
Switching (GMPLS) Signaling Resource ReserVation
ProtocolTraffic Engineering (RSVPTE) Extensions", RFC
3473, January 2003.
[RFC3985] Bryant, S., Ed., and P. Pate, Ed., "Pseudo Wire Emulation
EdgetoEdge (PWE3) Architecture", RFC 3985, March 2005.
[RFC4090] Pan, P., Ed., Swallow, G., Ed., and A. Atlas, Ed., "Fast
Reroute Extensions to RSVPTE for LSP Tunnels", RFC 4090,
May 2005.
[RFC4110] Callon, R. and M. Suzuki, "A Framework for Layer 3
ProviderProvisioned Virtual Private Networks (PPVPNs)",
RFC 4110, July 2005.
[RFC4972] Vasseur, JP., Ed., Leroux, JL., Ed., Yasukawa, S.,
Previdi, S., Psenak, P., and P. Mabbey, "Routing
Extensions for Discovery of Multiprotocol (MPLS) Label
Switch Router (LSR) Traffic Engineering (TE) Mesh
Membership", RFC 4972, July 2007.
[RFC5036] Andersson, L., Ed., Minei, I., Ed., and B. Thomas, Ed.,
"LDP Specification", RFC 5036, October 2007.
[MP2PRSVP] Yasukawa, Y., "Supporting MultipointtoPoint Label
Switched Paths in Multiprotocol Label Switching Traffic
Engineering", Work in Progress, October 2008.
[MPLSSEC] Fang, L., Ed., "Security Framework for MPLS and GMPLS
Networks", Work in Progress, November 2008.
Authors' Addresses
Seisho Yasukawa
NTT Corporation
911, MidoriCho 3Chome
MusashinoShi, Tokyo 1808585 Japan
Phone: +81 422 59 4769
EMail: s.yasukawa@hco.ntt.co.jp
Adrian Farrel
Old Dog Consulting
EMail: adrian@olddog.co.uk
Olufemi Komolafe
Cisco Systems
96 Commercial Street
Edinburgh
EH6 6LX
United Kingdom
EMail: femi@cisco.com
