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Performance Evaluation of QoS-CAODV, CAODV
Routing Protocol in Cognitive Radio Ad-hoc
Network
MALLAT Yosra
Research Unit MEDIATRON,
Higher School Of communication of Tunisia (Sup’Com)
TUNIS, TUNISIA
yosra.mallat@supcom.tn
AYARI Aymen
Research Unit MEDIATRON.
Higher School Of communication of Tunisia (Sup’Com)
TUNIS, TUNISIA
aymen.ayari@supcom.rnu.tn
AYADI Mohamed
Research Unit MEDIATRON,
Higher School Of communication of Tunisia (Sup’Com)
TUNIS, TUNISIA
m.ayadi@supcom.rnu.tn
TABAANE Sami
Research Unit MEDIATRON,
Higher School Of communication of Tunisia (Sup’Com)
TUNIS, TUNISIA
sami.tabbane@supcom.rnu.tn
Abstract— A large number of routing protocols for Cognitive
Radio (CR) have been recently proposed to improve the
efficiency of spectrum utilization. As an example, we can find
the Cognitive Ad hoc On demand Distance Vector (CAODV).
This protocol is based on AODV one and uses an on-demand
approach for finding routes to which the principals of regions
activity avoidance of the Primary User (PU) has been added
during the packet transfer. The main drawback of this
protocol is that it doesn’t support the Quality of Service (QoS)
mechanisms. In this paper, we propose to develop, implement
and test a new protocol that integrate the QoS adaption
mechanism in cognitive on demand routing protocol. The new
protocol, called QoS-CAODV, is a combination of QoS-AODV
and CAODV. The performances of QoS-CAODV protocol
have been evaluated by numerical simulations (OPNET 14.5).
We have observed from results that the QoS-CAODV protocol
provides better performance in term of average throughput,
end-to-end delay and gives the smallest number of dropped
packets.
Keywords— Cognitive Radio (CR), CAODV, QoS-CAODV,
routing protocol, OPNET 14.5 simulator.
I. INTRODUCTION
Recent studies on Cognitive Radio (Le-Thanh and Bao,
2011; Long and al., 2011; De-Domenico and al., 2012;
Sadeghi and al., 2012) have focused on detecting unused
spectrum. Nevertheless, a wireless ad-hoc network is a good
architecture to explore routing protocols in CR.
Consequently, a number of routing protocols have been
proposed and implemented for Cognitive Radio Ad Hoc
Networks (CRAHNs) (Cacciapuoti and al. 2010; Pefkianakis
and al. 2008; Kiam Cheng How and Maode Ma,2010;
Kaushik , al. 2010; Ding and al. 2010; Ma, H., Zheng, L.
2008; Weilian Su and Ian F. Akyildiz ; A.Cagatay Talay and
D. Turagy Altilar 2009) [5] [9]. It is important that routing
protocols include QoS metrics in route finding and
maintenance to retain end to end QoS. The ad hoc routing
protocols have two routing approaches: proactive (or table-
driven) and reactive (or on-demand) routing protocols [11].
Many revisions are done, for example, to the traditional
AODV protocol [10] to add QoS challenges. In this case, we
can introduce the Cognitive Ad hoc On demand Distance
Vector (CAODV). It uses an on-demand approach [8] which
assesses the qualities of any available channel, minimizing
the route cost by performing a common path and channel
selection for each forwarder. The main difficulty of this
protocol is it doesn’t maintain the QoS mechanisms.
Therefore, we are motivated to propose a new protocol
CAODV-QoS which integrates the QoS mechanism in
cognitive on demand routing protocol. Our new protocol
QoS-CAODV combines QoS-AODV and CAODV
protocol. It provides better performance in term of end-to-
end delay, average throughput and a small number of
dropped packets. All those are evaluated by the simulator
(OPNET 14.5). The rest of this article is organized as
follows: section 2 introduces a brief description of AODV,
QoS-AODV and CAODV protocol. In Section 3, the
performance evaluations using OPNET 14.5 is presented in
details (the simulation environment, the metrics and the
results of simulation). Finally, the conclusion of this article
is in section 4.
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II. BACKGROUND
In this article, on-demand routing protocols applicable for
CRAHNs are classified and reviewed.
A. AODV (Ad hoc On-demand Distance Vector)protocol:
The AODV protocol [1] is a reactive routing protocol
based on the distance vector principle, combining unicast
and multicast routing. In AODV, the path between two
nodes is calculated when it’s needed, i.e. when a source
node wants to send data packets to a destination, it finds a
path (Discovery Phase), uses it during the transfer phase,
and it must maintain this path during its utilization
(Maintenance Phase). The finding and maintaining process
of a path is based on the exchange set of control packets:
RREQ (Route REQueset), RREP (Route Reply), RERR
(Route Error) and Hello messages (Hello).
Fig. 1. Example of AODV protocol.
B. CAODV (Cognitive AODV)protocol:
The CAODV protocol [2] (Cacciapuoti et al. 2010) is
inspired from the AODV protocol. It has some
modifications. These modifications are:
• Whenever a node needs route to a destination, it
broadcasts RREQ by amending spectrum related
information in it that includes the best available
channel.
• An intermediate (SU) node that receives RREQ
checks whether it is in contact with a PU. If yes, it
simply adds information about the free spectrum
and broadcasts the packet further till it reaches its
destination or an intermediate node that has
information about the destination as well as the
spectrum in its routing table. If no channel is
available so, it simply drops the RREQ.
• The destination node chooses the best possible path
by taking he best and the shortest path from all
feasible paths that it receives.
C. QoS AODV:
The majority of routing protocols for Ad Hoc networks,
such as AODV, are designed without considering in an
explicit way the QoS of the routes that they generate. QoS
routing needs not only to find a route from the source to the
destination, but also a route that satisfies as a final constraint
like bandwidth, delay, throughput, latency, loss of packages,
etc.[6]
The qAODV (Quality of service AODV) [6] protocol
increases packet delivery ratio, reduces end to end delay and
moderates high mobility. The routing load of qAODV is a
little bit higher than traditional AODV.
In QoS-AODV (Quality of service AODV) [6], the AODV
protocol is extended by adding new domains: maximum
delay and minimum bandwidth extension. Special messages,
QoS LOST messages, are sent to all sources potentially
affected by the variation of QoS parameters. QoS-AODV
guarantees packet delivery ratio, normalizes the overhead
load and average latency in mobility.
The QAODV (Quality of service AODV) [6] protocol is an
extension of AODV protocol based on bandwidth and delay
constraints. It has two efficient route recovery mechanisms
for QoS routing.. QAODV reduces control overhead, delay,
improves end-to end delivery ratio and connection setup
latency.
The SQ-AODV (Stability-based QoS-capable AODV) [6]
protocol is an improvement AODV protocol. It has two
norms: how residual node energy is used for route selection
and how protocol can be rapidly adapted to network
conditions.
These protocols use only local information at each node
without adding any considerable overhead in the network.
So, we propose a new routing protocol referred to a QoS
Cognitive Ad-hoc On demand Distance Vector (QoS-
CAODV) protocol. It is based on a combination between
QoS-AODV and CAODV. This proposal avoids regions of
PU activity during both route formation and packet
discovery without demanding any dedicated control
channel. It exploits the presence of multiple available
channels to improve the overall performances.
III. Proposed work
This modification is done in our code to introduce QoS-
CAODV protocol for CRAHNs. The network is anticipated
to guarantee a set of pre-specified QoS attributes to the
users in terms of available bandwidth and end-to-end
performance. In fact, the classic CAODV routing protocol
can be modified. It adds the related QoS information to each
node in its routing table. When a path discovery process is
initiated, calculating the matching QoS conditions values
and finally we can find path with the best QoS condition. A
key to offer these QoS conditions is to find a route to the
preferred destination that can, with high probability, survive
for the duration of the session.
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Fig2. Diagram of QoS-CAODV protocol
IV. Performance evaluation
A. Simulation environment:
In this section, we evaluate the performances of our
proposed protocol, QoS-CAODV, by simulations via
OPNET 14.5. We carry out a multitude of tests with random
topology where 36 SUs and 10 PUs are randomly placed in
500x500 m.
Table I Standard parameter for simulation
After a defined time interval, the nodes start their
movement according to a mobility model random way point
and a moving speed varying between 0 and 17 m/s
maximum speed. Each simulation is run for 4000 sec.
Simulation’s parameters are summarized in the table I.
B. Simulation results
From simulation results in figures, it is observed that the
performance of our protocol QoS-CAODV is better than
other cognitive on-demand routing protocols (such as
CAODV), because of the proper receiving of packets and
less packet dropped. The QoS-CAODV gives the best
performance regarding to the packet transmission over the
different channel.
1) Average throughput analysis:
In Fig 3, we observed that QoS-CAODV provides
higher average throughput than CAODV. The QoS-
CAODV always creates more robust path for data delivery
and, as a result, it reduces the number of dropped packets
caused by the interference of PU activity. The CAODV has
a lower throughput than the QoS-CAODV due to higher
drop rates (the throughput difference between both protocol
is 0,69 bit/sec).
Fig3. Throughput vs time
2) Average end-to-end delay analysis:
In Fig 4, we observed that the delay in QoS-CAODV is
minor, which indicates that this protocol presents better
quality of service than CAODV protocol. It shows that the
average value of delay is almost 0.018 seconds for CAODV,
0.006 seconds for CAODV-QoS, After 3 minutes, it drops
and attains a constant value of 0.005 seconds for CAODV,
0.002 seconds for CAODV-QoS.
Parameters Value
Simulator OPNET 14.5
Protocol studied CAODV, QoS-CAODV
Simulation time 4000sec
Simulation Area 500 x 500 m
Mobility Model random way point
Modulation DPSK
N primary node 10 nodes
N secondary node 36 nodes
speed 17 m/s
throughput 5,5 mb/s
Buffer size 256 000 bits
Transmit power 0.005 w
Channel type Wireless channel
Bandwidth 22.000 khz
Data rate 1000 kb/s
Packet size 1024 bits
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Fig4. Average end-to-end delay vs time
The CAODV protocol has a long delay because their route
discovery takes more time as the optimal path is selected.
3) The Route Discovery Time analysis:
Having considered the achieved results in Fig.5, we see
that the Route Discovery Time in QoS-CAODV has been
decreased compared to similar conditions in CAODV
routing.
Fig 5. Route Discovery Time vs time
4) The Data Dropped analysis:
In Fig 6, we see that the number of deleted packets in
QoS-CAODV routing has been decreased compared to the
CAODV protocol. Some packets have been buffered in
nodes because their needed resources and will be deleted
after their life cycle.
Fig6.Data Dropped vs time
Fig 6 shows that the average value of Data Dropped is 2000
bit/seconds for CAODV and 800 bit/ seconds for CAODV-
QoS, After 3 minutes, it drops to 200 bit/seconds for
CAODV and approximately 50 bit/seconds for CAODV-
QoS.
5) The Total Route Errors Sent analysis:
The route errors sent is caused by the repeated packet
of route request for a particular route in which the route
may be broken or will be moved out of active route because
the needed resources have not been supplied.
Fig 7. Total Route Errors Sent vs time
In Fig.7, the simulation results achieved less total route
errors sent request for CAODV-QoS, 1.8 routes compared
to 1.6 routes for CAODV routing.
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6) The Total Route Replies Sent analysis:
Total Route Replies Sent represents total number of
route reply packets sent from all nodes in the network if
they are destinations of route requests.
Fig 8. Total Route Replies Sent vs time
From Fig 8, it is clear that CAODV consistently have more
route replies sent from destination than CAODV-QoS which
is due to less probability of route errors and packets dropped
in CAODV-QoS.
7) The Media Access Delay analysis:
This delay is calculated as the duration from the time
when it is inserted into the transmission queue until the time
when the frame is sent to the physical layer for the first
time.
Fig 9. Media Access Delay (Sec) vs time
In Fig 9, it shows that the average value of Media Access
Delay is almost 0.022 seconds for CAODV, 0.010 seconds
for CAODV QoS. After 3 minutes, it gradually drops and
attains a constant value of approximately 0.002 seconds for
CAODV QoS, 0.004 seconds for CAODV.
V. CONCLUSION
In this article, we present the implementation and the test
of a new protocol, QoS-CAODV, that illustrates the
adaptation of QoS concept in cognitive on demand routing
protocol. It is a mixing between QoS-AODV and CAODV (
is based on AODV and uses an on-demand approach). Our
simulation work illustrates the performance of the QoS-
CAODV routing protocols in term of some metrics such as
throughput, end-to-end delay, less route replies sent, less
route discovery time and small number of dropped packets
and route error sent. As perspective, we can test our
protocol according to different technologies like WIMAX,
LTE 5G...
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