QUALITY OF SERVICE ISSUES FOR MULTISERVICE IP
NETWORKS
Matej Kavacký, Erik Chromý, Lenka Krulikovská and Juraj Pavlovič
Department of Telecommunications, Faculty of Electrical Engineering and Information Technology
Slovak University of Technology, Ilkovičova 3, 812 19 Bratislava, Slovak Republic
Keywords: Admission control, Bandwidth constraint model, Quality of Service.
Abstract: Our paper deals with utilization of Quality of Service (QoS) mechanisms for backbone IP network capable
of transport of voice, data and video services. The first part presents selected QoS mechanisms for
multiservice IP networks. The next part discusses impact of selected QoS mechanisms on multimedia traffic
through simulations. In the final part we have proposed combination of QoS methods for selected network
configuration.
1 INTRODUCTION
The convergence of networks and services brings
new opportunities for delivering of services. One of
these opportunities is the delivery of Triple Play
packages. The network operators provide voice,
television and data services through single access to
provider and single transport network. Until recently
each of these services was delivered through its own
network which met the requirements on quality of
transmission for particular service (telephone
network, television, internet). Single universal
network has to be capable of transmitting of these
services with the respect of their quality of service
requirements. In our work we have focused on
preventive traffic control through admission control
(AC) methods for IP networks (Más, 2008) and
Bandwidth Constraints (BC) models (Faucheur,
2005), (Ash, 2005) of QoS Differentiated Services
(DiffServ) architecture.
2 ADMISSION CONTROL
The main task of admission control methods is to
accept new traffic flow only if the network can
guarantee the QoS parameters of the new flow and
the admission of this flow will not degrade QoS of
existing flows. Also the efficient utilization of the
network resources is the goal of admission control
methods. Various AC methods for IP networks were
proposed in the literature, i.e. Bandwidth Broker
based AC, Measurement based AC, Probe based AC
(Bohnert, 2007). We have aimed to Measurement
based AC (MBAC) due to their simple
implementation and acceptable computational
requirements. We will focus on Measured Sum and
Effective Bandwidth based admission algorithms.
3 SIMULATION MODEL
The QoS mechanisms have been simulated for one
100 Mbit/s link of backbone IP/MPLS network.
Simulations were performed in open source Network
Simulator 2.29. It is object oriented simulator of
discrete events with focus on telecommunication
networks. We have divided our simulations into
three parts:
 simulations without QoS mechanisms,
 simulations with bandwidth constraint models
(MAM, RDM),
 application of MBAC Measured Sum method
on video traffic.
Simulation time was set to 8 seconds. We have to
note that this time does not correspond to real
situation, but it is sufficient for demonstration of
behavior of network and QoS mechanisms.
Parameters of Voice over IP (VoIP), Video on
Demand (VoD) and data traffic are set in Table 1.
Traffic flows were set for simulation needs so that
link overload and high packet losses will occur.
Input traffic is shown in Table 2.
185
Kavacky M., Chromý E., Krulikovská L. and Pavlovi
ˇ
c J. (2009).
QUALITY OF SERVICE ISSUES FOR MULTISERVICE IP NETWORKS.
In Proceedings of the International Conference on Signal Processing and Multimedia Applications, pages 185-188
DOI: 10.5220/0002221901850188
Copyright
c
 SciTePress

Table 1: Traffic parameters.
Traffic
type
Codec Required
bandwidth
per flow
Packet
length
VoIP G.729 8 kbit/s 10 B
VoD MPEG-4 6 Mbit/s 100 B
Data n/a Unrestricted 100 B
Table 2: Input traffic flows.
Traffic
flows
Total
capacity
[Mbit/s]
Start time
[s]
Flow
duration
[s]
1 x Data 70 0 5
3 x VoD 18 1 3
6 x VoD 36 1.5 3
1000 x
VoIP
8 2 2
2 x VoD 12 2.5 2
1 x Data 70 3 5
10 x VoD 60 5.5 2
4 SIMULATION RESULTS
4.1 Simulation without QoS
In this simulation scenario the traffic flows are not
prioritized, all flows are treated as equivalent. In the
case of link overload every flow is degraded without
respect of its QoS requirements. The results of
simulation are shown in the table 3, where R
represents total transmitted packets, D is number of
dropped packets and L is percentual loss for whole
link and particular traffic types. We can see that total
packet loss without utilization of QoS mechanisms is
28.45%. Packet losses for each type of traffic are
comparable, the slightly higher loss of video traffic
is due to its start when the network is overloaded. In
the Figure 1 we can see link throughput during our
simulation. After link overload each flow compete
for required link capacity. Total link utilization
reached 90.83%.
Table 3: Transmitted and dropped packets without QoS
mechanisms. R - transmitted packets, D - dropped packets,
L - loss.
Packets D R L [%]
VoIP
57473 142526 28.74
VoD
117204 265293 30.64
Data
237451 628797 27.41
Total
412128 1036616 28.45
4.2 Simulations with BC Models
This scenario illustrates the use of Bandwidth
Constraint models as QoS mechanism in IP/MPLS
network. We have studied the network behavior
when MAM or RDM model (Faucheur, 2005) is
implemented and their efficiency during link
overload and congestion. We have divided traffic
into three classes according priorities. For each class
we have assign bandwidth determined during system
design. We have used following traffic classes and
their parameters:
 VoIP traffic – priority 1 (the highest),
reserved bandwidth 9 Mbit/s,
 VoD traffic – priority 2, reserved bandwidth
36 Mbit/s,
 Data traffic – priority 3 (the lowest), reserved
bandwidth 55 Mbit/s.
4.2.1 Simulation with MAM Model
Maximum Allocation Bandwidth Constraints Model
(MAM) is based on strict maximum bandwidth
allocation. The main principle of MAM model is to
strict allocation of maximal bandwidth for defined
traffic class. The simulation results for this model
are presented in the Table 4 and Figure 2. From the
table IV we can see that loss of VoIP packets
dropped to 0%, but the packet losses of other traffic
classes have been increased. It is due to each flow
has allocated certain capacity that can be used, but
nor exceeded even if there is spare bandwidth on the
link. The behavior of MAM model is obvious in the
figure 2 from 4.5 to 5.0 seconds when only 70
Mbit/s flows are active, but they share only 55
Mbit/s of bandwidth, while the total bandwidth is
100 Mbit/s. The similar example is in time interval 0
– 1 s when only one 70 Mbit/s flow is
accommodated on the link and which uses only
allocated bandwidth of 55 Mbit/s. This approach
leads to inefficient utilization of network resources.
The link utilization is decreased to 79.83%.
Table 4: Transmitted and dropped packets for MAM
model. R - transmitted packets, D - dropped packets, L -
loss.
Packets D R L [%]
VoIP
0 199999 0
VoD
142978 239449 37.39
Data
327342 538897 37.79
Total
470320 978345 32.47
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186

Figure 1: Throughput of particular flows without
utilization of QoS mechanisms.
4.2.2 Simulation with RDM Model
Russian Dolls Bandwidth Constraints Model (RDM)
model offers cumulative sharing of bandwidth
among various traffic classes. Simulation results for
RDM model are presented in the Table 5 and Figure
3. We can see that the VoIP were transmitted again
without losses, but contrary to MAM model, the loss
of data flows and total link loss are better than in the
case of MAM model. RDM model allows sharing of
unused bandwidth, so traffic flows can exceed their
allocated bandwidth. But only flows with the lower
priority are allowed to exceed allocated bandwidth.
This behavior is obvious in the figure 3 from 4.5 to
5.0 seconds when two traffic flows use the whole
link bandwidth even though they have allocated only
55 Mbit/s. Another example can be seen in time
interval 0 – 1 s when one 70 Mbit/s flow with
assigned 55 Mbit/s bandwidth uses full 70 Mbit/s.
The use of RDM model leads to more efficient
utilization of network resources. The link utilization
is now increased to 90.88%. Based on the previous
simulation results we have decided to use RDM
model in our system proposal due to better link
bandwidth utilization and bandwidth guarantee for
each of services.
Table 5: Transmitted and dropped packets for RDM
model.
Packets D R L [%]
VoIP
0 199999 0
VoD
142810 239687 37.34
Data
217162 649086 25.07
Total
359972 1088772 24.85
Figure 2: Throughput of particular flows with
implementation of MAM model.
4.3 Simulation with MBAC for Video
Traffic
With the regard of simulation results of RDM model
simulation we have to improve loss of VoD packets,
which reached almost 40%. For VoD traffic we have
allocated bandwidth of 36 Mbit/s, but during almost
the whole simulation the bandwidth required by
active VoD connections exceeded this limit. Hence
we have decided to use MBAC method for video
traffic. We have compared three MBAC methods
(Measured Sum, Effective Bandwidth based on
Hoeffding Bounds and Tangent at Peak) by
simulations. Based on these simulations we have
decided to use Measured Sum method (Nevin, 2008)
because it has reached several times zero packet
loss. The number of sampling periods per time
window n we have set to 10 and allowable link
utilization is 100%. The simulation results we can
see in the Table 6 and in the Figure 4.
We can observe that packet loss of VoIP traffic is
unchanged by Measured Sum method compared to
previous simulation. Application of Measured Sum
admission control method has impact on the packet
loss of VoD traffic, which has now zero value.
It is due to rejection of connections exceeding the
allocated bandwidth by their requirements. The
packet loss of data traffic is also decreased, because
MS method accepts less of VoD connections, so the
data flows can use bandwidth dedicated to VoD
traffic. Total link utilization reached 90.88% and
Table 6: Transmitted and dropped packets for RDM model
with Measured Sum MBAC for VoD traffic.
Packets D R L [%]
VoIP
0 199999 0
VoD
0 224999 0
Data
202482 663766 23.37
Total
202482 1088764 15.86
QUALITY OF SERVICE ISSUES FOR MULTISERVICE IP NETWORKS
187

Figure 3: Throughput of particular flows with
implementation of RDM model.
Figure 4: Throughput of particular flows with
implementation of RDM model and Measured Sum
method for VoD traffic.
total packet loss dropped to 15.68%. It is not
necessary to add additional QoS mechanisms,
because we have reached zero losses for the services
with the higher QoS requirements. Admission
control Measured Sum method can be applied also
on VoIP traffic. We have met the QoS requirements
of VoIP by RDM model by dividing of bandwidth
among particular traffic classes.
5 CONCLUSIONS
Internet Protocol networks naturally offer only best-
effort service. Hence, many different QoS
mechanisms for IP networks have been proposed.
We have verified two of these mechanisms for the
multiservice IP network by simulations.
Based on our simulations we have proposed efficient
combination of measurement based admission
control and bandwidth constraint model for QoS
provision for voice, video and data services
transmitted over single IP network.
ACKNOWLEDGEMENTS
This work is a part of research activities conducted
at Department of Telecommunications FEI STU
Bratislava, within the scope of scope of the project
VEGA No. 1/0565/09.
REFERENCES
Ash, J. 2005. RFC 4126 - Max Allocation with
Reservation Bandwidth Constraints Model for
DiffServ-aware MPLS Traffic Engineering, The
Internet Society.
Bohnert, T. 2007. Admission Control for Packet
Newtorks. University of Coimbra, Portugal. Retrieved
December 10, 2008, from
http://tmb.nginet.de/public/ac_lecture.pdf
Chao, J., Gou, X. 2002. Quality of Service in High Speed
Networks, John Wiley & Sons, New York. ISBN 0-
471-00397-2.
Faucheur, F., Lai, W. 2005. RFC 4125 - Maximum
Allocation Bandwidth Constraints Model for DiffServ-
aware MPLS Traffic Engineering, The Internet
Society.
Faucheur, F. 2005. RFC 4127 – Russian Dolls Bandwidth
Constraints Model for DiffServ-aware MPLS Traffic
Engineering, The Internet Society.
Halás, M., Kyrbashov, B., Kováčik, M. 2008. Influence of
encryption on VoIP connection quality. In 9
th
International Conference Research in
Telecommunication Technology 2008, Vyhne, Slovak
Republic, September 10 – 12, 2008, ISBN 978-80-
227-2939-0.
Más, I. 2008. On Admission Control for IP Networks
Based on Probing, Royal Institute of Technology.
Stockholm, ISBN 978-91-7415-012-4.
Medvecký, M. 2007. Performance of BC Models for QoS
provisioning in MPLS. In International Conference
Research in Telecommunication Technology (RTT)
2007. University of Žilina, pp. 245-250, ISBN 978-80-
8070-735-4.
Nevin, A., Jiang, Y., Emstad, P. 2008. Robustness Study
of MBAC Algorithms. In IEEE Symposium on
Computers and Communications (ISCC) 2008. IEEE
Computer Society, pp. 1040 – 1046, ISBN 978-1-
4244-2702-4.
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