Proceedings of the 2007 IEEE International Conference on Telecommunications and
Malaysia International Conference on Communications, 14-17 May 2007, Penang, Malaysia
Bandwidth Sharing Scheme in DiffServ-aware MPLS Networks
Norashidah Md Din*, Hazlinda Hakimie* and Norsheila Fisalη
*
Department of Electrical Engineering, College of Engineering, Universiti Tenaga Nasional,
KM 7, Jalan Kajang-Puchong, 43009 Kajang, Selangor, Malaysia
{ norashidah, hazlinda}@uniten.edu.my
η
Telekom’s Laboratory, Faculty of Electrical Engineering
Universiti Teknologi Malaysia, 81310 Skudai, Johor Bahru, Malaysia
sheila@ fke.utm.my
technology can complement it in providing the service
differentiation required. By mapping the DiffServ traffic to
the MPLS LSPs, DiffServ-aware MPLS networks can treat the
traffic according to the traffic class.
Bandwidth constraint models have been proposed for
DiffServ-aware MPLS environment [5, 6 and 7]. This work
proposes an implementation using Russian Dolls bandwidth
allocation model. Section II covers related work in bandwidth
allocation models whereas Section III describes the bandwidth
sharing algorithm with Russian Dolls bandwidth allocation
model. Section IV discusses the simulation work and Section
V the conclusion.
Abstract— This paper proposes a bandwidth sharing
scheme for DiffServ-aware MPLS networks based on the Russian
Dolls bandwidth allocation model. Three DiffServ traffic class
types were used in the DiffServ-aware MPLS network under
study, i.e. real time constant bit rate premium, real time variable
bit rate assured and non-real time best effort traffic. We propose
a preemption scheme based on rerouting or resizing of the
longest existing flow first. A simulation study using ns-2 was
performed for the scheme. An analysis was made to show the
significance of borrowing and preemption in the environment.
The results show significant improvement in terms of blocking
probability when both borrowing and preemption are used.
Keywords—DiffServ, Triple Play, Russian Doll, ,Bandwidth Sharing
Preemption
II. BANDWIDTH ALLOCATION MODELS
I. INTRODUCTION
Currently, three bandwidth constraint models for DiffServenabled MPLS traffic engineering have been provisioned in
IETF. The first is the maximum allocation bandwidth
constraints model as described in RFC 4125 [5] consist of
allocation of bandwidth constraint for each traffic class and a
maximum reserved bandwidth value normally associated to
link capacity. The summation of the bandwidth constraints
can exceed the maximum reserved bandwidth. The higher
priority traffic can preempt the lower priority traffic to get
their full allocated bandwidth. For example, in a scenario
where voice traffic class is allocated a bandwidth constraint of
1.5Gbps, data traffic class is allocated a bandwidth constraint
of 2.0 Gbps and the maximum reserved bandwidth is
allocated 3.0 Gbps, the aggregate of voice and data traffic
would then be limited to 3.0Gbps. The voice LSPs always has
higher preemption priority in order to use the 1.5 Gbps
capacity. The voice LSPs will preempt the data LSPs to
Traffic engineering is essential for optimum use of
transmission capacity and making networks resilient so that
they can withstand link or node failures. Multiprotocol Label
Switching (MPLS) [1, 2 and 3], traffic engineering ideally
routes traffic flows across a network based on the resources
the traffic flow requires and the resources available in the
network. Path preemption is also possible in MPLS where an
existing path can be discontinued so that a higher priority path
may be established. The path taken can be reserved through a
signalling protocol like RSVP-TE or by using constraintbased routing. RSVP-TE establishes Label Switched Paths
(LSPs) in MPLS through path reservation. Constraint-based
routing on the other hand ascertains a path that satisfies some
constraints of interest like delay, jitter, throughput or loss
besides finding for the shortest path only.
An important feature of MPLS is the ability to set up LSPs
for different services. Differentiated Services (DiffServ) [4]
1-4244-1094-0/07/$25.00 ©2007 IEEE.
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classes of multimedia traffic, i.e. real time constant bit rate
traffic or premium traffic, real time variable bit rate traffic or
assured rate traffic and non real time variable bit rate traffic
or best effort traffic. The premium traffic is associated with
the DiffServ’s Expedited Forwarding Per Hop Behaviour (EF
PHB)[9] and assured rate traffic is associated with Assured
Forwarding Per Hop Behavioue (AF PHB) [10]. Whereas the
best effort traffic is known as BE PHB which corresponds to
the traffic of the traditional Internet.
achieve this. The data LSPs can use up to link capacity of the
bandwidth left by the voice LSPs.
The second model is the maximum allocation plus
bandwidth reservation and protection mechanism as defined in
RFC 4126 [6] model is similar to the maximum allocation
bandwidth constraints model above in that a maximum
bandwidth allocation is given to each traffic class type.
However, through the use of bandwidth reservation and
protection mechanisms, each traffic class type is only allowed
to exceed their bandwidth allocations under conditions of no
congestion and need to their allocated bandwidths when
overload and congestion occurs.
The third model introduced was the Russian Dolls
bandwidth constraints model as outlined in RFC 4127 [7]
consist of allocation of bandwidth constraint for each traffic
class with a maximum of eight class types. The maximum
allowable bandwidth usage is done cumulatively by grouping
successive class types according to priority class. A lower
priority class can use higher priority class bandwidth up to the
summation of their bandwidth constraints values. The higher
priority traffic can preempt the lower priority traffic to get
their full allocated bandwidth. For example, in a scenario
where voice traffic class is allocated a bandwidth constraint of
1.5Gbps, data traffic class is allocated a bandwidth constraint
of 3.0 Gbps, the aggregate of voice and data traffic would then
be limited to 3.0Gbps. The voice LSPs are confined to 1.5
Gbps capacity. The voice LSPs will preempt the data LSPs
when necessary to achieve this. The data LSPs can use up to
link capacity of the bandwidth left by the voice LSPs.
In RFC 4128 [8], a performance analysis for the Russian
Dolls and maximum allocation models are described. The
general theme of the investigation is the trade-off between
bandwidth sharing to achieve greater efficiency under normal
conditions, and to achieve robust class protection/isolation
under overload. The Russian Dolls model was found to allow
greater sharing of bandwidth among different classes and
performs somewhat better under normal conditions. On the
other hand the maximum allocation model does not depend on
the use of preemption. However, it provides more robust class
isolation under overload. It was concluded in the study that
the use of preemption gives higher-priority traffic some
degree of immunity to the overloading of other classes. This
results in a higher blocking/preemption for the overloaded
class than that in a pure blocking environment.
In this work we propose a bandwidth sharing scheme based on
EF
EF
AF
Ingress
Egress
AF
BE
BE
Fig. 1: DiffServ-aware MPLS Network Model
For admission into the network, each of the traffic flow is
allocated a bandwidth value at the ingress node. Each of the
EF and AF real time traffic flows are allocated bandwidth
according to their peak rate whereas the BE traffic flows are
allocated their mean rate.
Bandwidth sharing is based on the Russian Dolls bandwidth
allocation model. The RDM used in this work follow the
following mode:
•
All LSPs with EF PHB use no more than 40% of access
bandwidth
•
All LSPs from EF and AF PHBs use no more than 80%
of access bandwidth
•
All LSPs from EF, AF and BE PHBs use no more than
100% of access bandwidth
The access bandwidth per class in the Russian Dolls Model
(RDM) is illustrated in Fig. 2. The bandwidth range for each
traffic class is shown in Table 1. The lower priority traffic can
borrow from the higher priority traffic and the higher priority
traffic is able to preempt the lower priority traffic based on the
rerouting or resizing of the lower priority traffic first. Resizing
occurs for AF traffic since they are of the adaptive rate like
MPEG-4 type traffic and rerouting for BE traffic.
The RDM pseudocode with preemption is as follows:
preemption by rerouting best effort traffic or resizing adaptive rate
assured forwarding traffic class. Thee longest lower priority traffic
existing flow will be preempted first.
1
2
3
III. ADMISSION AND BANDWIDTH SHARING
4
5
The DiffServ-aware MPLS network model used in this
work is shown in Fig. 1 is assumed able to cater for three
Set up simulation time= 3000s
Set traffic load
Set random arrival rate with mean average
required
Set random traffic life time with mean
average required
Configure network topology and traffic
parameters
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6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Continuously start EF, AF and BE sources
according to their arrival rates
Continuously terminate sources according
to their life time
Invoke the following admission control
process when a source start-time is invoked:
For new EF connection:
Proc new_traffic_EF
Calculate EF available bandwidth
Check if EF_new_connection_bw <=
available_EF_bw
If yes accept_EF_connection
else
if EF_new_connection_bw >
available_EF_bw
call RDM preemptor procedure
For new AF connection
Proc new_traffic_AF
Calculate AF available bandwidth
Check if AF_new_connection_bw <=
available_AF_bw
If yes accept_AF_connection
else
if AF_new_connection_bw >
available_∑EF+AF_bw
call RDM preemptor procedure
For new BE connection
Proc new_traffic_BE
Calculate BE available bandwidth
Check if BE_new_connection_bw <=
available_∑EF+AF+BE_bw
If yes accept_BE_connection
else
if BE_new_connection_bw >
available_∑EF+AF+BE _bw
reject_BE_connection
Proc RDM preemptor
Preempt or Reroute flows based on
longest existing flow first
If no flows to preempt or reroute, then
reject connection
borrow from EF and AF traffic class. However, it cannot
preempt any other flows and is rejected if it has no available
bandwidth and no bandwidth to borrow.
Available
Access
Bandwidth
EF
40%
BE
100%
AF
80%
Fig. 2: Access Bandwidth Allocation
Table 1: Bandwidth Range
% EF
PHB
traffic
40
% AF PHB
traffic
Min Max
40
80
% BE PHB
traffic
Min Max
20
100
IV. SIMULATION STUDY
A simulation study was carried out for the proposed
bandwidth sharing scheme based on the network model of Fig.
1 using ns-2 network simulator [11]. There are 11 nodes in the
network, i.e. 3 sources, 3 sinks and 5 MPLS nodes. The
bandwidth between links is 3Mbps. Each of the admitted
traffic would be assigned an LSP based on class. The LSP
will be based on peak rate value for EF traffic, adaptive rate
for AF traffic and mean bandwidth for BE traffic.
The performance metric used in evaluating the bandwidth
sharing scheme is the blocking probability at the ingress node.
The blocking probability is obtained for various offered traffic
load by dividing the sum of rejected flows over total number
of admission request. An offered traffic load is a measure
obtained by dividing the mean traffic arrival rate,λ, over the
mean service rate, µ, i.e. λ/µ Erlang. The mean service rate
can be obtained by taking the inverse of the mean holding or
service time. The basic traffic descriptions are given in Table
2. All simulation runs take 3000s to completely eliminate any
transient effect as suggested by [12]. The network model for
Lines 1-7 describe the traffic and network set up. The arrival
and termination of traffic flows are randomly done using
Poisson distribution. Upon connection admission request the
admission control will be invoked depending on class type the
appropriate procedure will trigger. For the EF traffic class it
cannot borrow but will preempt AF and BE traffic class by
preempting the longest existing flow first as shown in lines
10-16. On the other hand, the AF traffic class can borrow
from EF traffic class and preempt longer existing AF flows or
BE flows as in lines 17-25. Lines 26-32 show the admission
control flow for BE admission request. BE traffic class can
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the simulation work was validated using Erlang loss formula
[13].
11
12
Table 2 Traffic Description
13
14
15
16
17
18
19
20
21
22
23
To study the performance of the fuzzy regulator, the EF
premium traffic is first gradually admitted to the DiffServaware MPLS network from a smaller to a bigger offered
traffic load, i.e. 1 to 9 Erlangs, whereas the assured and best
effort offered traffic load are fixed with 50 Erlangs
respectively. Then, the simulation work is repeated but with
the AF traffic varied from 1 to 9 Erlangs and the EF and BE
traffic are held constant at 50 Erlangs. This is then again
repeated with BE traffic class varied from 1 to 9 Erlangs and
the AF and BE class held constant at 50 Erlangs. The mean
arrival rates and mean holding time used are given in Table 3.
The values are arbitrarily chosen but they provide heavy load
conditions where borrowing exists so that preemption is
relevant.
Once a connection is accepted, it would be assigned an LSP
using shortest path route. The simulation work comprise of
RDM admission control investigation with and without
preemption. When it is without preemption, only borrowing is
allowed whereas with preemption the higher priority traffic
can claim back its allocated bandwidth by rerouting and
resizing the lower priority traffic based on earliest flow first.
The RDM without preemption pseudocode is as follows:
1
2
3
4
5
6
7
8
9
10
24
25
26
27
28
29
30
31
32
Calculate EF available bandwidth
Check if EF_new_connection_bw <=
available_EF_bw
If yes accept_EF_connection
else
if EF_new_connection_bw >
available_EF_bw
reject_EF_connection
For new AF connection
Proc new_traffic_AF
Calculate EF and AF available bandwidth
Check if AF_new_connection_bw <=
available_AF_bw
If yes accept_AF_connection
else
if AF_new_connection_bw >
available_∑EF+AF_bw
reject_AF_connection
For new BE connection
Proc new_traffic_BE
Calculate EF,BE and AF available
bandwidth
Check if BE_new_connection_bw <=
available_∑EF+AF+BE_bw
If yes accept_BE_connection
else
if BE_new_connection_bw >
available_∑EF+AF+BE _bw
reject_BE_connection
The traffic and network set up are similar to ones with
preemption, i.e. lines 1-7, and the arrival and termination of
traffic flows are also randomly done using Poisson
distribution. Similarly also, at the beginning of a connection
arrival, admission control will take place and the appropriate
procedure will trigger based on connection class type. For the
EF traffic class it cannot borrow and cannot preempt as in
lines 10-16. The AF traffic class can borrow from EF traffic
class but cannot preempt any flows 17-24. Again BE traffic
class can borrow from EF and AF traffic class but cannot
preempt any flows as illustrated in lines 25-32.
Fig. 3 shows the blocking performance when the EF traffic
is gradually increased from 1 to 9 Erlangs, and AF and BE
traffic are held constant at 50 Erlangs. The EF with RDM
preemption (EF-P) has 20-30% better blocking compared to
EF without RDM preemption (EF-NP). The AF with RDM
preemption (AF-P) also shows better blocking performance.
by about 5%. For BE traffic class no blocking were
experienced for the simulation with and without preemption
since BE traffic can borrow bandwidth and would be rerouted
when preempted.
Fig. 4 provides the blocking performance when the AF
traffic is gradually increased from 1 to 9 Erlangs, and EF and
Set up simulation time= 3000s
Set traffic load
Set random arrival rate with mean average
required
Set random traffic life time with mean
average required
Configure network topology and traffic
parameters
Continuously start EF, AF and BE sources
according to their arrival rates
Continuously terminate sources according
to their life time
Invoke the following admission control
process when a source start-time is invoked:
For new EF connection:
Proc new_traffic_EF
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BE traffic is held constant at 50 Erlangs. The EF-P with a
constant 50 Erlangs traffic has about 5% better blocking
compared to EF-NP. As the AF traffic is being increased we
see that blocking increases. The AF with RDM preemption
(AF-P) shows 20% better blocking performance. Again for
BE traffic no blocking were experienced for the simulation
with and without preemption since BE traffic can borrow
bandwidth and would be rerouted when preempted.
Fig. 4 provides the blocking performance when the AF
traffic is gradually increased from 1 to 9 Erlangs, and EF and
BE traffic is held constant at 50 Erlangs. The EF-P with a
constant 50 Erlangs traffic has about 5% better blocking
compared to EF-NP. As the AF traffic is being increased we
see that blocking increases. The AF with RDM preemption
(AF-P) shows 20% better blocking performance. Again for
BE traffic no blocking were experienced for the simulation
with and without preemption since BE traffic can borrow
bandwidth and would be rerouted when preempted.
Fig. 5 provides the blocking performance when the BE
traffic is gradually increased from 1 to 9 Erlangs, and EF and
AF traffic is held constant at 50 Erlangs. No difference is
detected in the EF-P and EF-NP blockings when BE traffic is
increased. This is because the increased in the BE traffic class
does not effect the constant load EF flows. The AF traffic
provides significant lowering of the blocking probability of
about 80% at 9 Erlangs when BE traffic is increased. The BE
with no preemption (BE-NP) blocking is seen to increase as
the BE offered load increases whereas the BE with
preemption (BE-P) experienced almost no blocking. This is
again attributed to the BE-P being able to borrow and
preempted through rerouting.
1.0
Blocking
0.8
0.6
EF-NP
EF-P
0.4
AF-NP
AF-P
0.2
BE-NP
BE-P
0.0
1
3
EF-NP
0.8
Blocking
EF-P
AF-NP
0.6
AF-P
BE-NP
0.4
0.8
0.0
BE-P
1
Blocking
9
1.0
0.2
EF-NP
3
5
7
BE Offered Traffic (Erlang)
9
Fig. 5 Blocking Probability when EF Offered Traffic is
increased
EF-P
AF-NP
0.4
7
Fig. 4 Blocking Probability when AF Offered Traffic is
increased
1.0
0.6
5
AF Offered Traffic (Erlang)
AF-P
BE-NP
0.2
V. CONCLUSISON
BE-P
This paper looks at bandwidth sharing in the DiffServaware MPLS network based on the RDM model. Bandwidth
borrowing is allowed by the lower priority traffic and limited
by their respective cumulative bandwidth constraints whereas
bandwidth preemption is based on preempting of higher to
lower priority traffic. We propose that bandwidth preemption
be based on resizing adaptive variable bit rate traffic and
rerouting of best effort elastic Internet traffic. Results show
that borrowing and preemption can form the basis of
0.0
1
3
5
7
9
EF Offered Traffic (Erlang)
Fig. 3 Blocking Probability when EF Offered Traffic is
increased
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bandwidth sharing in a DiffServ-aware MPLS network as
oppose to have a borrowing only. We see equal or better
performance, i.e. up to 80%, in blocking probability when the
preemption scheme was in place.
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[13]
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