<- RFC Index (4801..4900)
RFC 4829
Network Working Group J. de Oliveira, Ed.
Request for Comments: 4829 Drexel University
Category: Informational JP. Vasseur, Ed.
Cisco Systems, Inc.
L. Chen
Verizon Laboratories
C. Scoglio
Kansas State University
April 2007
Label Switched Path (LSP) Preemption Policies for
MPLS Traffic Engineering
Status of This Memo
This memo provides information for the Internet community. It does
not specify an Internet standard of any kind. Distribution of this
memo is unlimited.
Copyright Notice
Copyright (C) The IETF Trust (2007).
IESG Note
This RFC is not a candidate for any level of Internet Standard. The
IETF disclaims any knowledge of the fitness of this RFC for any
purpose and, in particular, notes that the decision to publish is not
based on IETF review for such things as security, congestion control,
or inappropriate interaction with deployed protocols. The RFC Editor
has chosen to publish this document at its discretion. Readers of
this document should exercise caution in evaluating its value for
implementation and deployment. See RFC 3932 for more information.
Abstract
When the establishment of a higher priority (Traffic Engineering
Label Switched Path) TE LSP requires the preemption of a set of lower
priority TE LSPs, a node has to make a local decision to select which
TE LSPs will be preempted. The preempted LSPs are then rerouted by
their respective Head-end Label Switch Router (LSR). This document
presents a flexible policy that can be used to achieve different
objectives: preempt the lowest priority LSPs; preempt the minimum
number of LSPs; preempt the set of TE LSPs that provide the closest
amount of bandwidth to the required bandwidth for the preempting TE
LSPs (to minimize bandwidth wastage); preempt the LSPs that will have
the maximum chance to get rerouted. Simulation results are given and
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a comparison among several different policies, with respect to
preemption cascading, number of preempted LSPs, priority, wasted
bandwidth and blocking probability is also included.
Table of Contents
1. Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. LSP Setup Procedure and Preemption . . . . . . . . . . . . . . 5
4. Preemption Cascading . . . . . . . . . . . . . . . . . . . . . 6
5. Preemption Heuristic . . . . . . . . . . . . . . . . . . . . . 7
5.1. Preempting Resources on a Path . . . . . . . . . . . . . . 7
5.2. Preemption Heuristic Algorithm . . . . . . . . . . . . . . 8
6. Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
6.1. Simple Case: Single Link . . . . . . . . . . . . . . . . . 10
6.2. Network Case . . . . . . . . . . . . . . . . . . . . . . . 12
7. Security Considerations . . . . . . . . . . . . . . . . . . . 16
8. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 16
9. Informative References . . . . . . . . . . . . . . . . . . . . 17
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1. Motivation
The IETF Traffic Engineering Working Group has defined the
requirements and protocol extensions for DiffServ-aware MPLS Traffic
Engineering (DS-TE) [RFC3564] [RFC4124]. Several Bandwidth
Constraint models for use with DS-TE have been proposed [RFC4127]
[RFC4128] [RFC4126] and their performance was analyzed with respect
to the use of preemption.
Preemption can be used as a tool to help ensure that high priority
LSPs can always be routed through relatively favorable paths.
Preemption can also be used to implement various prioritized access
policies as well as restoration policies following fault events
[RFC2702].
Although not a mandatory attribute in the traditional IP world,
preemption becomes important in networks using online, distributed
Constrained Shortest Path First (CSPF) strategies for their Traffic
Engineering Label Switched Path (TE LSP) path computation to limit
the impact of bandwidth fragmentation. Moreover, preemption is an
attractive strategy in an MPLS network in which traffic is treated in
a differentiated manner and high-importance traffic may be given
special treatment over lower-importance traffic [DEC-PREP, ATM-PREP].
Nevertheless, in the DS-TE approach, whose issues and requirements
are discussed in [RFC3564], the preemption policy is considered an
important piece on the bandwidth reservation and management puzzle,
but no preemption strategy is defined. Note that preemption also
plays an important role in regular MPLS Traffic Engineering
environments (with a single pool of bandwidth).
This document proposes a flexible preemption policy that can be
adjusted in order to give different weight to various preemption
criteria: priority of LSPs to be preempted, number of LSPs to be
preempted, amount of bandwidth preempted, blocking probability. The
implications (cascading effect, bandwidth wastage, priority of
preempted LSPs) of selecting a certain order of importance for the
criteria are discussed for the examples given.
2. Introduction
In [RFC2702], issues and requirements for Traffic Engineering in an
MPLS network are highlighted. In order to address both traffic-
oriented and resource-oriented performance objectives, the authors
point out the need for priority and preemption parameters as Traffic
Engineering attributes of traffic trunks. The notion of preemption
and preemption priority is defined in [RFC3272], and preemption
attributes are defined in [RFC2702] and [RFC3209].
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A traffic trunk is defined as an aggregate of traffic flows belonging
to the same class that are placed inside an LSP [RFC3564]. In this
context, preemption is the act of selecting an LSP that will be
removed from a given path in order to give room to another LSP with a
higher priority (lower preemption number). More specifically, the
preemption attributes determine whether an LSP with a certain setup
preemption priority can preempt another LSP with a lower holding
preemption priority from a given path, when there is competition for
available resources. Note that competing for resources is one
situation in which preemption can be triggered, but other situations
may exist, themselves controlled by a policy.
For readability, a number of definitions from [RFC3564] are repeated
here:
Class-Type (CT): The set of Traffic Trunks crossing a link that is
governed by a specific set of Bandwidth constraints. CT is used for
the purposes of link bandwidth allocation, constraint-based routing,
and admission control. A given Traffic Trunk belongs to the same CT
on all links.
TE-Class: A pair of:
i. A Class-Type.
ii. A preemption priority allowed for that Class-Type. This means
that an LSP transporting a Traffic Trunk from that Class-Type can use
that preemption priority as the set-up priority, as the holding
priority, or both.
By definition, there may be more than one TE-Class using the same CT,
as long as each TE-Class uses a different preemption priority. Also,
there may be more than one TE-Class with the same preemption
priority, provided that each TE-Class uses a different CT. The
network administrator may define the TE-Classes in order to support
preemption across CTs, to avoid preemption within a certain CT, or to
avoid preemption completely, when so desired. To ensure coherent
operation, the same TE-Classes must be configured in every Label
Switched Router (LSR) in the DS-TE domain.
As a consequence of a per-TE-Class treatment, the Interior Gateway
Protocol (IGP) needs to advertise separate Traffic Engineering
information for each TE-Class, which consists of the Unreserved
Bandwidth (UB) information [RFC4124]. The UB information will be
used by the routers, checking against the bandwidth constraint model
parameters, to decide whether preemption is needed. Details on how
to calculate the UB are given in [RFC4124].
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3. LSP Setup Procedure and Preemption
A new LSP setup request has two important parameters: bandwidth and
preemption priority. The set of LSPs to be preempted can be selected
by optimizing an objective function that represents these two
parameters, and the number of LSPs to be preempted. More
specifically, the objective function could be any, or a combination,
of the following [DEC-PREP, ATM-PREP]:
* Preempt the LSPs that have the least priority (preemption
priority). The Quality of Service (QoS) of high priority traffic
would be better satisfied, and the cascading effect described below
can be limited.
* Preempt the least number of LSPs. The number of LSPs that need to
be rerouted would be lower.
* Preempt the least amount of bandwidth that still satisfies the
request. Resource utilization could be improved. The preemption
of larger TE LSPs (more than requested) by the newly signaled TE
LSP implies a larger amount of bandwidth to be rerouted, which is
likely to increase the probability of blocking (inability to find a
path for some TE LSPs).
* Preempt LSPs that minimize the blocking probability (risk that
preempted TE LSP cannot be rerouted).
After the preemption selection phase is finished, the selected LSPs
are signaled as preempted and the new LSP is established (if a new
path satisfying the constraints can be found). The UB information is
then updated via flooding of an IGP-TE update and/or simply pruning
the link where preemption occurred. Figure 1 shows a flowchart that
summarizes how each LSP setup request is treated in a preemption-
enabled scenario.
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LSP Setup Request
(TE-Class i, bw=r)
|
|
v NO
UB[TE-Class i] >= r ? -------> Reject LSP
Setup and flood an updated IGP-TE
| LSA/LSP
|YES
v NO
Preemption Needed ? -------> Setup LSP/Update UB if a threshold is
| crossed
| YES
v
Preemption ----> Setup LSP/Reroute Preempted LSPs
Algorithm Update UB
Figure 1: Flowchart for LSP setup procedure.
In [DEC-PREP], the authors propose connection preemption policies
that optimize the discussed criteria in a given order of importance:
number of LSPs, bandwidth, and priority; bandwidth, priority, and
number of LSPs. The novelty in our approach is the use of an
objective function that can be adjusted by the service provider in
order to stress the desired criteria. No particular criteria order
is enforced. Moreover, a new criterion is added to the objective
function: optimize the blocking probability (to minimize the risk
that an LSP is not rerouted after being preempted).
4. Preemption Cascading
The decision of preempting an LSP may cause other preemptions in the
network. This is called preemption cascading effect and different
cascading levels may be achieved by the preemption of a single LSP.
The cascading levels are defined in the following manner: when an LSP
is preempted and rerouted without causing any further preemption, the
cascading is said to be of level zero. However, when a preempted LSP
is rerouted, and in order to be established in the new route it also
causes the preemption of other LSPs, the cascading is said to be of
level 1, and so on.
Preemption cascading is not desirable and therefore policies that
minimize it are of interest. Typically, this can result in severe
network instabilities. In Section 5, a new versatile preemption
heuristic will be presented. In Section 6, preemption simulation
results will be discussed and the cascading effect will be analyzed.
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5. Preemption Heuristic
5.1. Preempting Resources on a Path
It is important to note that once a request for an LSP setup arrives,
each LSR along the TE LSP path checks the available bandwidth on its
outgoing link. For the links in which the available bandwidth is not
enough, the preemption policy needs to be activated in order to
guarantee the end-to-end bandwidth reservation for the new LSP. This
is a distributed approach, in which every node on the path is
responsible for running the preemption algorithm and determining
which LSPs would be preempted in order to fit the new request. A
distributed approach may not lead to an optimal solution.
Alternatively, in a centralized approach, a manager entity runs the
preemption policy and determines the best LSPs to be preempted in
order to free the required bandwidth in all the links that compose
the path. The preemption policy would try to select LSPs that
overlap with the path being considered (preempt a single LSP that
overlaps with the route versus preempt a single LSP on every link
that belongs to the route).
Both centralized and distributed approaches have advantages and
drawbacks. A centralized approach would be more precise, but require
that the whole network state be stored and updated accordingly, which
raises scalability issues. In a network where LSPs are mostly
static, an offline decision can be made to reroute LSPs and the
centralized approach could be appropriate. However, in a dynamic
network in which LSPs are set up and torn down in a frequent manner
because of new TE LSPs, bandwidth increase, reroute due to failure,
etc., the correctness of the stored network state could be
questionable. Moreover, the setup time is generally increased when
compared to a distributed solution. In this scenario, the
distributed approach would bring more benefits, even when resulting
in a non-optimal solution (The gain in optimality of a centralized
approach compared to a distributed approach depends on many factors:
network topology, traffic matrix, TE strategy, etc.). A distributed
approach is also easier to be implemented due to the distributed
nature of the current Internet protocols.
Since the current Internet routing protocols are essentially
distributed, a decentralized approach was selected for the LSP
preemption policy. The parameters required by the new preemption
policies are currently available for OSPF and Intermediate System to
Intermediate System (IS-IS).
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5.2. Preemption Heuristic Algorithm
Consider a request for a new LSP setup with bandwidth b and setup
preemption priority p. When preemption is needed, due to lack of
available resources, the preemptable LSPs will be chosen among the
ones with lower holding preemption priority (higher numerical value)
in order to fit r=b-Abw(l). The variable r represents the actual
bandwidth that needs to be preempted (the requested, b, minus the
available bandwidth on link l: Abw(l)).
L is the set of active LSPs having a holding preemption priority
lower (numerically higher) than p. So L is the set of candidates for
preemption. b(l) is the bandwidth reserved by LSP l in L, expressed
in bandwidth units, and p(l) is the holding preemption priority of
LSP l.
In order to represent a cost for each preemption priority, an
associated cost y(l) inversely related to the holding preemption
priority p(l) is defined. For simplicity, a linear relation
y(l)=8-p(l) is chosen. y is a cost vector with L components, y(l). b
is a reserved bandwidth vector with dimension L, and components b(l).
Concerning the objective function, four main objectives can be
reached in the selection of preempted LSPs:
* minimize the priority of preempted LSPs,
* minimize the number of preempted LSPs,
* minimize the preempted bandwidth,
* minimize the blocking probability.
To have the widest choice on the overall objective that each service
provider needs to achieve, the following equation was defined (for
simplicity chosen as a weighted sum of the above mentioned criteria):
H(l)= alpha y(l) + beta 1/b(l) + gamma (b(l)-r)^2 + theta b(l)
In this equation:
- alpha y(l) captures the cost of preempting high priority LSPs.
- beta 1/b(l) penalizes the preemption of low bandwidth LSPs,
capturing the cost of preempting a large number of LSPs.
- gamma (b(l)-r)^2 captures the cost of preemption of LSPs that are
much larger or much smaller than r.
- theta b(l) captures the cost of preempting large LSPs.
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Coefficients alpha, beta, gamma, and theta can be chosen to emphasize
one or more components of H.
The coefficient theta is defined such that theta = 0 if gamma > 0.
This is because when trying to minimize the blocking probability of
preempted LSPs, the heuristic gives preference to preempting several
small LSPs (therefore gamma, which is the weight for minimizing the
preempted bandwidth enforcing the selection of LSPs with similar
amount of bandwidth as the requested, needs to be set as zero). The
selection of several small LSPs in a normally loaded portion of the
network will increase the chance that such LSPs are successfully
rerouted. Moreover, the selection of several small LSPs may not
imply preempting much more than the required bandwidth (resulting in
low-bandwidth wastage), as it will be seen in the discussed examples.
When preemption is to happen in a heavy loaded portion of the
network, to minimize blocking probability, the heuristic will select
fewer LSPs for preemption in order to increase the chance of
rerouting.
H is calculated for each LSP in L. The LSPs to be preempted are
chosen as the ones with smaller H that add enough bandwidth to
accommodate r. When sorting LSPs by H, LSPs with the same value for
H are ordered by bandwidth b, in increasing order. For each LSP with
repeated H, the algorithm checks whether the bandwidth b assigned to
only that LSP is enough to satisfy r. If there is no such LSP, it
checks whether the bandwidth of each of those LSPs added to the
previously preempted LSPs' bandwidth is enough to satisfy r. If that
is not true for any LSP in that repeated H-value sequence, the
algorithm preempts the LSP that has the larger amount of bandwidth in
the sequence, and keeps preempting in decreasing order of b until r
is satisfied or the sequence is finished. If the sequence is
finished and r is not satisfied, the algorithm again selects LSPs to
be preempted based on an increasing order of H. More details on the
algorithm are given in [PREEMPTION].
When the objective is to minimize blocking, the heuristic will follow
two options on how to calculate H:
* If the link in which preemption is to happen is normally loaded,
several small LSPs will be selected for preemption using H(l)=
alpha y(l) + theta b(l).
* If the link is overloaded, few LSPs are selected using H(l)= alpha
y(l) + beta 1/b(l).
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6. Examples
6.1. Simple Case: Single Link
We first consider a very simple case, in which the path considered
for preemption is composed by a single hop. The objective of this
example is to illustrate how the heuristic works. In the next
section, we will study a more complex case in which the preemption
policies are being tested on a network.
Consider a link with 16 LSPs with reserved bandwidth b in Mbps,
preemption holding priority p, and cost y, as shown in Table 1. In
this example, 8 TE-Classes are active. The preemption here is being
performed on a single link as an illustrative example.
------------------------------------------------------------------
LSP L1 L2 L3 L4 L5 L6 L7 L8
------------------------------------------------------------------
Bandwidth (b) 20 10 60 25 20 1 75 45
Priority (p) 1 2 3 4 5 6 7 5
Cost (y) 7 6 5 4 3 2 1 3
------------------------------------------------------------------
LSP L9 L10 L11 L12 L13 L14 L15 L16
------------------------------------------------------------------
Bandwidth (b) 100 5 40 85 50 20 70 25
Priority (p) 3 6 4 5 2 3 4 7
Cost (y) 5 2 4 3 6 5 4 1
------------------------------------------------------------------
Table 1: LSPs in the considered link.
A request for an LSP establishment arrives with r=175 Mbps and p=0
(highest possible priority, which implies that all LSPs with p>0 in
Table 1 will be considered when running the algorithm). Assume
Abw(l)=0.
If priority is the only important criterion, the network operator
configures alpha=1, beta=gamma=theta=0. In this case, LSPs L6, L7,
L10, L12, and L16 are selected for preemption, freeing 191 bandwidth
units to establish the high-priority LSP. Note that 5 LSPs were
preempted, but all with a priority level between 5 and 7.
In a network in which rerouting is an expensive task to perform (and
the number of rerouted TE LSPs should be as small as possible), one
might prefer to set beta=1 and alpha=gamma=theta=0. LSPs L9 and L12
would then be selected for preemption, adding up to 185 bandwidth
units (less wastage than the previous case). The priorities of the
selected LSPs are 3 and 5 (which means that they might themselves
preempt some other LSPs when rerouted).
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Suppose the network operator decides that it is more appropriate to
configure alpha=1, beta=10, gamma=0, theta=0 (the parameters were set
to values that would balance the weight of each component, namely
priority and number, in the cost function), because in this network
rerouting is very expensive, LSP priority is important, but bandwidth
is not a critical issue. In this case, LSPs L7, L12, and L16 are
selected for preemption. This configuration results in a smaller
number of preempted LSPs when compared to the first case, and the
priority levels are kept between 5 and 7.
To take into account the number of LSPs preempted, the preemption
priority, and the amount of bandwidth preempted, the network operator
may set alpha > 0, beta > 0, and gamma > 0. To achieve a balance
among the three components, the parameters need to be normalized.
Aiming for a balance, the parameters could be set as alpha=1, beta=10
(bringing the term 1/b(l) closer to the other parameters), and
gamma=0.001 (bringing the value of the term (b(l)-r)^2 closer to the
other parameters). LSPs L7 and L9 are selected for preemption,
resulting in exactly 175 bandwidth units and with priorities 3 and 7
(note that less LSP are preempted but they have a higher priority
which may result in a cascading effect).
If the minimization of the blocking probability is the criterion of
most interest, the cost function could be configured with theta=1,
alpha=beta=gamma=0. In that case, several small LSPs are selected
for preemption: LSPs L2, L4, L5, L6, L7, L10, L14, and L16. Their
preemption will free 181 Mbps in this link, and because the selected
LSPs have small bandwidth requirement there is a good chance that
each of them will find a new route in the network.
From the above example, it can be observed that when the priority was
the highest concern and the number of preempted LSPs was not an
issue, 5 LSPs with the lowest priority were selected for preemption.
When only the number of LSPs was an issue, the minimum number of LSPs
was selected for preemption: 2, but the priority was higher than in
the previous case. When priority and number were important factors
and a possible waste of bandwidth was not an issue, 3 LSPs were
selected, adding more bandwidth than requested, but still with low
preemption priority. When considering all the parameters but the
blocking probability, the smallest set of LSP was selected, 2, adding
just enough bandwidth, 175 Mbps, and with priority levels 3 and 7.
When the blocking probability was the criterion of interest, several
(8) small LSPs were preempted. The bandwidth wastage is low, but the
number of rerouting events will increase. Given the bandwidth
requirement of the preempted LSPs, it is expected that the chances of
finding a new route for each LSP will be high.
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6.2. Network Case
For these experiments, we consider a 150 nodes topology with an
average network connectivity of 3. 10% of the nodes in the topology
have a degree of connectivity of 6. 10% of the links are OC3, 70% are
OC48, and 20% are OC192.
Two classes of TE LSPs are in use: Voice LSPs and Data Internet/VPN
LSPs. For each class of TE LSP, the set of preemptions (and the
proportion of LSPs for each preemption) and the size distributions
are as follows (a total of T LSPs is considered):
T: total number of TE LSPs in the network (T = 18,306 LSPs)
Voice:
Number: 20% of T
Preemption: 0, 1 and 2
Size: uniform distribution between 30M and 50M
Internet/VPN TE:
Number: 4% of T
Preemption: 3
Size: uniform distribution between 20M and 50M
Number: 8% of T
Preemption 4
Size: uniform distribution between 15M and 40M
Number: 8% of T
Preemption 5
Size: uniform distribution between 10M and 20M
Number: 20% of T
Preemption 6
Size: uniform distribution between 1M and 20M
Number: 40% of T
Preemption 7
Size: uniform distribution between 1K and 1M
LSPs are set up mainly due to network failure: a link or a node
failed and LSPs are rerouted.
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The network failure events were simulated with two functions:
- Constant: 1 failure chosen randomly among the set of links every 1
hour.
- Poisson process with interarrival average = 1 hour.
Table 2 shows the results for simulations with constant failure. The
simulations were run with the preemption heuristic configured to
balance different criteria (left side of the table), and then with
different preemption policies that consider the criteria in a given
order of importance rather than balancing them (right side of the
table).
The proposed heuristic was configured to balance the following
criteria:
HPB: The heuristic with priority and bandwidth wastage as the most
important criteria (alpha=10, beta=0, gamma=0.001, theta=0).
HBlock: The heuristic considering the minimization of blocking
probability (normal load links: alpha=1, beta=0, gamma=0, theta=0.01)
(heavy load links: alpha=1, beta=10).
HNB: The heuristic with number of preemptions and wasted bandwidth in
consideration (alpha=0, beta=10, gamma=0.001, theta=0).
Other algorithms that consider the criteria in a given order of
importance:
P: Sorts candidate LSPs by priority only.
PN: Sorts the LSPs by priority, and for cases in which the priority
is the same, orders those LSPs by decreasing bandwidth (selects
larger LSPs for preemption in order to minimize number of preempted
LSPs).
PB: Sorts the LSPs by priority, and for LSPs with the same priority,
sorts those by increasing bandwidth (select smaller LSPs in order to
reduce bandwidth wastage).
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-------------------------------------------------
| Heuristic | Other algorithms |
-------------------------------------------------
| HPB | HBlock| HNB | P | PN | PB |
-----------------------------------------------------------------
Need to be | 532 | 532 | 532 | 532 | 532 | 532 |
Rerouted | | | | | | |
-----------------------------------------------------------------
Preempted | 612 | 483 | 619 | 504 | 477 | 598 |
-----------------------------------------------------------------
Rerouted |467|76%|341|73%|475|77%|347|69%|335|70%|436|73%|
Blocked |145|24%|130|27%|144|23%|157|31%|142|30%|162|27%|
-----------------------------------------------------------------
Max Cascading | 4.5 | 2 | 5 | 2.75 | 2 | 2.75 |
-----------------------------------------------------------------
Wasted Bandwidth| | | | | | |
AVR (Mbps) | 6638 | 532 | 6479 | 8247 | 8955 | 6832 |
Worst Case(Mbps)| 35321 |26010 |36809 | 28501 | 31406 | 23449 |
-----------------------------------------------------------------
Priority | | | | | | |
Average | 6 | 6.5 | 5.8 | 6.6 | 6.6 | 6.6 |
Worst Case | 1.5 | 3.8 | 1.2 | 3.8 | 3.8 | 3.8 |
-----------------------------------------------------------------
Extra Hops | | | | | | |
Average | 0.23 | 0.25 | 0.22 | 0.25 | 0.25 | 0.23 |
Worst Case | 3.25 | 3 | 3.25 | 3 | 3 | 2.75 |
-----------------------------------------------------------------
Table 2: Simulation results for constant network failure:
1 random failure every hour.
From Table 2, we can conclude that among the heuristic (HPB, HBlock,
HNB) results, HBlock resulted in the smaller number of LSPs being
preempted. More importantly, it also resulted in an overall smaller
rejection rate and smaller average wasted bandwidth (and second
overall smaller worst-case wasted bandwidth.)
Although HBlock does not try to minimize the number of preempted
LSPs, it ends up doing so, because it preempts LSPs with lower
priority mostly, and therefore it does not propagate cascading much
further. Cascading was the overall lowest (preemption caused at most
two levels of preemption, which was also the case for the policy PN).
The average and worst preemption priority was very satisfactory
(preempting mostly lowest-priority LSPs, like the other algorithms P,
PN, and PB).
When HPB was in use, more LSPs were preempted as a consequence of the
higher cascading effect. That is due to the heuristic's choice of
preempting LSPs that are very similar in bandwidth size to the
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bandwidth size of the preemptor LSP (which can result in preempting a
higher priority LSP and therefore causing cascading). The wasted
bandwidth was reduced when compared to the other algorithms (P, PN,
PB).
When HNB was used, cascading was higher than the other cases, due to
the fact that LSPs with higher priority could be preempted. When
compared to P, PN, or PB, the heuristic HNB preempted more LSPs (in
fact, it preempted the largest number of LSPs overall, clearly
showing the cascading effect), but the average wasted bandwidth was
smaller, although not as small as HBlock's (the HNB heuristic tries
to preempt a single LSP, meaning it will preempt LSPs that have a
reserved bandwidth similar to the actual bandwidth needed. The
algorithm is not always successful, because such a match may not
exist, and in that case, the wasted bandwidth could be high). The
preempted priority was the highest on average and worse case, which
also shows why the cascading level was also the highest (the
heuristic tries to select LSPs for preemption without looking at
their priority levels). In summary, this policy resulted in a poor
performance.
Policy PN resulted in the small number of preempted LSPs overall and
small number of LSPs not successfully rerouted. Cascading is low,
but bandwidth wastage is very high (overall highest bandwidth
wastage). Moreover, in several cases in which rerouting happened on
portions of the network that were underloaded, the heuristic HBlock
preempted a smaller number of LSPs than PN.
Policy P selects a larger number of LSPs (when compared to PN) with
low priority for preemption, and therefore it is able to successfully
reroute less LSPs when compared to HBlock, HPB, HNB, or PN. The
bandwidth wastage is also higher when compared to any of the
heuristic results or to PB, and it could be worse if the network had
LSPs with a low priority and large bandwidth, which is not the case.
Policy PB, when compared to PN, resulted in a larger number of
preempted LSPs and an overall larger number of blocked LSPs (not
rerouted), due to preemption. Cascading was slightly higher. Since
the selected LSPs have low priority, they are not able to preempt
much further and are blocked when the links are congested. Bandwidth
wastage was smaller since the policy tries to minimize wastage, and
preempted priority was about the same on average and worst case.
The simulation results show that when preemption is based on
priority, cascading is not critical since the preempted LSPs will not
be able to propagate preemption much further. When the number of
LSPs is considered, fewer LSPs are preempted and the chances of
rerouting increases. When bandwidth wastage is considered, smaller
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LSPs are preempted in each link and the wasted bandwidth is low. The
heuristic seems to combine these features, yielding the best results,
especially in the case of blocking probability. When the heuristic
was configured to minimize blocking probability (HBlock), small LSPs
with low priority were selected for preemption on normally loaded
links and fewer (larger) LSPs with low priority were selected on
congested links. Due to their low priority, cascading was not an
issue. Several LSPs were selected for preemption, but the rate of
LSPs that were not successfully rerouted was the lowest. Since the
LSPs are small, it is easier to find a new route in the network.
When selecting LSPs on a congested link, fewer larger LSPs are
selected improving load balance. Moreover, the bandwidth wastage was
the overall lowest. In summary, the heuristic is very flexible and
can be configured according to the network provider's best interest
regarding the considered criteria.
For several cases, the failure of a link resulted in no preemption at
all (all LSPs were able to find an alternate path in the network) or
resulted in preemption of very few LSPs and subsequent successfully
rerouting of the same with no cascading effect.
It is also important to note that for all policies in use, the number
of extra hops when LSPs are rerouted was not critical, showing that
preempted LSPs can be rerouted on a path with the same length or a
path that is slightly longer in number of hops.
7. Security Considerations
The practice described in this document does not raise specific
security issues beyond those of existing TE.
8. Acknowledgements
We would like to acknowledge the input and helpful comments from
Francois Le Faucheur (Cisco Systems) and George Uhl (Swales
Aerospace).
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9. Informative References
[ATM-PREP] Poretsky, S. and Gannon, T., "An Algorithm for
Connection Precedence and Preemption in Asynchronous
Transfer Mode (ATM) Networks", Proceedings of IEEE ICC
1998.
[DEC-PREP] Peyravian, M. and Kshemkalyani, A. D. , "Decentralized
Network Connection Preemption Algorithms", Computer
Networks and ISDN Systems, vol. 30 (11), pp. 1029-1043,
June 1998.
[PREEMPTION] de Oliveira, J. C. et al., "A New Preemption Policy for
DiffServ-Aware Traffic Engineering to Minimize
Rerouting", Proceedings of IEEE INFOCOM 2002.
[RFC2702] Awduche, D., Malcolm, J., Agogbua, J., O'Dell, M., and
J. McManus, "Requirements for Traffic Engineering Over
MPLS", RFC 2702, September 1999.
[RFC3209] Awduche, D., Berger, L., Gan, D., Li, T., Srinivasan,
V., and G. Swallow, "RSVP-TE: Extensions to RSVP for
LSP Tunnels", RFC 3209, December 2001.
[RFC3272] Awduche, D., Chiu, A., Elwalid, A., Widjaja, I., and X.
Xiao, "Overview and Principles of Internet Traffic
Engineering", RFC 3272, May 2002.
[RFC3564] Le Faucheur, F. and W. Lai, "Requirements for Support
of Differentiated Services-aware MPLS Traffic
Engineering", RFC 3564, July 2003.
[RFC4124] Le Faucheur, F., "Protocol Extensions for Support of
Diffserv-aware MPLS Traffic Engineering", RFC 4124,
June 2005.
[RFC4126] Ash, J., "Max Allocation with Reservation Bandwidth
Constraints Model for Diffserv-aware MPLS Traffic
Engineering & Performance Comparisons", RFC 4126,
June 2005.
[RFC4127] Le Faucheur, F., "Russian Dolls Bandwidth Constraints
Model for Diffserv-aware MPLS Traffic Engineering",
RFC 4127, June 2005.
de Oliveira, et al. Informational [Page 17]
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[RFC4128] Lai, W., "Bandwidth Constraints Models for
Differentiated Services (Diffserv)-aware MPLS Traffic
Engineering: Performance Evaluation", RFC 4128,
June 2005.
Authors' Addresses
Jaudelice C. de Oliveira (editor)
Drexel University
3141 Chestnut Street (ECE Dept.)
Philadelphia, PA 19104
USA
EMail: jau@ece.drexel.edu
JP Vasseur (editor)
Cisco Systems, Inc.
1414 Massachusetts Avenue
Boxborough, MA 01719
USA
EMail: jpv@cisco.com
Leonardo Chen
Verizon Laboratories
40 Sylvan Rd. LA0MS55
Waltham, MA 02451
USA
EMail: leonardo.c.chen@verizon.com
Caterina Scoglio
Kansas State University
2061 Rathbone Hall
Manhattan, Kansas 66506-5204
USA
EMail: caterina@eece.ksu.edu
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