Ijcet 06 09_004

http://www.iaeme.com/IJCIET/index.asp 32 editor@iaeme.com
International Journal of Computer Engineering & Technology (IJCET)
Volume 6, Issue 9, Sep 2015, pp. 32-41, Article ID: IJCET_06_09_004
Available online at
http://www.iaeme.com/IJCET/issues.asp?JType=IJCET&VType=6&IType=9
ISSN Print: 0976-6367 and ISSN Online: 0976–6375
© IAEME Publication
___________________________________________________________________________
SIMULATION BASED AND ANALYSIS OF
ROUTING PROTOCOLS FOR VANET
USING VANETMOBISIM AND NS-2
Vongpasith Phouthone
College of Information Science and Engineering,
Hunan University, 410082, Changsha, China
Wang Dong
College of Information Science and Engineering,
Hunan University, 410082, Changsha, China
ABSTRACT
Vehicular Ad hoc Network (VANET) is a distributed, self-organizing
communication networks built up by vehicles traveling on the streets; with
expected to benefit in safety applications, and disseminating real-time traffic
congestion. VANET is thus characterized by very high speeds and limited
degrees of freedom in nodes movement patterns, such particular features often
make standard networking protocols inefficient and effect on performance of
routing protocols. Therefore, routing protocols in VANET is become a
challenging task. This research paper analyzes routing protocol based on the
performance metrics like packet delivery ratio, average end-to-end delay and
throughput of the network under VANET environments using a network
simulator (Ns-2) for simulating network connection and VanetMobiSim for
generating the mobility pattern of vehicles. This experiment has provided
insight into the performance of routing protocols for urban random scenario.
Finding indicates simulation of different number of nodes only marginally
affected VANET routing performance in our experimental settings.
Key words: Ns-2, Routing Protocols, VANET, VanetMobiSim
Cite this Article: Vongpasith Phouthone and Wang Dong. Simulation Based
and Analysis of Routing Protocols for Vanet Using Vanetmobisim and Ns-2.
International Journal of Computer Engineering and Technology, 6(9), 2015,
pp. 32-41.
http://www.iaeme.com/IJCET/issues.asp?JType=IJCET&VType=6&IType=9

Simulation Based and Analysis of Routing Protocols for Vanet Using Vanetmobisim and Ns-2
1. INTRODUCTION
VANET is a distributed, self-organizing series of communication networks built up
by vehicles traveling on the streets, expected to benefit safety applications, gathering
and disseminating real-time traffic congestion and routing information, sharing of
wireless channels for mobile applications etc [1]. VANET is special case of Mobile
Adhoc Network (MANET), both MANET and VANET networks are multi hop
mobile networks with dynamic topology [2]. However, VANET is thus characterized
by very high speeds and limited degrees of freedom in nodes movement patterns [1],
such particular features often make standard networking protocols inefficient or
unusable and effect on performance of routing protocols. Therefore, networking
protocols in VANET become a challenging task, that is why a rich research in the
development of protocols specific for VANET is in progress. So far to improve the
routing performance and reliability, various protocols in VANET have been analyzed
using different parameters. In [3] [4][5][6] proactive and reactive protocols have been
compared based upon number of variables including: packets lost, average end-to-end
delay, average packet Jitter, packet delivery ratio and throughput of the network. In
the proposed works, the most efficient routing protocols to be used for different
applications has been identified based upon the results of the comparison. One of the
critical aspects when evaluating routing protocols for VANET is the employment of
the mobility pattern of vehicles also called the mobility model that reflect as closely
as possible the real behavior of vehicular traffic. Several studies in analyzing the
performance of routing protocols using different mobility models that are specific to
VANET have been published: In [7][8][9][10][13] demonstrate how the protocol
performance varies across different mobility models and how the performance
ranking of protocols may vary with the mobility model used. Deploying and testing
VANET involves high cost and manpower. Hence, simulation of VANET is a useful
methodology tool prior to actual implementation. In this paper we have analyzed
routing performance of DSDV, AODV and AOMDV routing protocol in simulation
based VANET environment using network simulator (Ns-2) to simulate network
connection and VanetMobiSim to generate the mobility pattern of vehicles with urban
random scenario. The performance evaluation is based on the metric of packet
delivery ratio, end to end delay and throughput of the network.
The rest of the paper is organized in the following manner: section 2 discuss about
the routing protocols for simulation. Simulation environments are presented in section
3. The simulation results are shown in section 4 and finally paper is concluded in the
section 5.
2. ROUTING PROTOCOLS FOR SIMULATION
The routing protocols basically perform the three main functionality route discovery,
maintenance and selection of the most efficient path from the various available paths.
The routing protocols in the VANET environment are characterized on the basis of
application where they are most suitable [3]. VANET routing protocols can be
classified as topology-based and geographic-based [11]. In this paper we focused on
only topology based routing protocols i.e. DSDV, AODV and AOMDV.

Vongpasith Phouthone and Wang Dong
Figure 1 Classification of VANET Routing Protocols [12]
2.1. Destination Sequenced Distance Vector Routing (DSDV)
DSDV [13] is a proactive, table-driven routing protocol scheme which is basically a
distance vector with small adjustments to make it better suited for ad hoc networks.
These adjustments consist of triggered updates that will take care of topology changes
in the time between broad casts [3]. In DSDV every node maintains a table of
information in the presence of every other node in the network. It update the table
periodically when change occurred in the network. If any change occur in the network
then it broadcasts to every node in the network [4].
2.2. Ad Hoc on Demand Distance Vector (AODV)
AODV establishes a route to a destination when there is a demand occurs for the
transmission of the data. It does not contain any loop [14]. AODV routing protocol
has consist a route request packet and a route reply packets < RREQ, RREP> pair of
message to find the route. The RREQ propagates through the network until it reaches
the destination or the node with a fresh enough route to the destination. Then the route
is made available by unceasing a RREP back to the source. AODV is only updates the
relevant neighboring node(s) instead of broadcasting every node of the network [1].
2.3. Ad Hoc on Demand Multipath Routing Protocol (AOMDV)
AOMDV [9] is an extension of a single path routing scheme AODV by computing
multiple paths during route discoveries. It allows to compute multiple loop free and
link disjoint paths between any source and destination nodes. In AOMDV, different
instances of RREQs are not discarded by intermediate nodes. The intermediate node
rebroadcasts the new RREQs to neighbor nodes. When the destination receives more
RREQ instances, in order to get multiple link disjoint routes, it replies with multiple
RREP messages.

3. SIMULATION ENVIRONMENTS
The main goal of this paper is to simulate and analyze the performance of the three
VANET routing protocols DSDV, AODV and AOMDV. There are the various tools
that are used for producing the realistic or random mobility model and simulation of
network traffic. For this paper it has been used software VanetMobiSim-1.1 and Ns-
2.35 to generate the vehicular trace file for network simulation and simulate network
connection between nodes respectively.
3.1. VanetMobiSim
The Vehicular Ad Hoc Networks Mobility Simulator (VanetMobiSim) is a set of
extensions to CanuMobiSim, a framework for user mobility modeling used by the
CANU (Communication in Ad Hoc Networks for Ubiquitous Computing) Research
Group. The framework includes a number of mobility models, as well as parsers for
geographic data sources in various formats, and a visualization module. The set of
extensions provided by VanetMobiSim consists mainly on a vehicular spatial model
which is created from topological data obtained in user defined, random, Geographic
Data Files (GDF) and TIGER/line Files. After that the vehicular specific spatial
elements such as multi lane and multi flow roads, stop signs and traffic lights are
added. The main component of the vehicular oriented model is the support of a
microscopic level mobility model named “Intelligent Driving Model with Intersection
Management (IDM_IM)” and IDM with Lane Changing (IDM LC) [15].
3.2 Ns-2
Ns-2 refer as network simulator (version 2) developed at UC Berkeley. It is a event
driven simulator and it is object oriented simulator in which code is written either in
C++ or in OCTL. It provides a packet level simulation over a lot of protocols,
supporting several transport protocols, several forms of multi-cast, wired networking,
several ad hoc routing protocols and propagation models, data broadcasting, satellite,
etc. It incorporates different traffic generators as web, telnet, CBR (constant bit rate
generator), etc. for using them in the simulations. Also, Ns-2 has the possibility of
using mobile nodes. The mobility of these nodes may be specified either directly in
the simulation file or by using a mobility trace file. It uses three types of files namely
Tool Command Language file (.tcl), Trace file (.tr) and Network Animator file
(.nam). Tool command language file (.tcl) has subsets of commands which are written
into it for simulation. While simulator runs on (.tcl), simulation trace file (.tr) and
animation file (.nam) are created during the session [16].
3.3 Simulation setup
The figure 2. represents the main scheme, in which is based from beginning to end the
processes for the simulation and results analysis.

Figure 2 Diagram of processes for obtaining the results
Firstly in the software VanetMobiSim-1.1, the scenario of vehicular traffic trace
file (*.tr) is generated. This trace is compatible with the network simulator Ns-2.35,
and is loaded together with the network traffic trace file (*.tr). Secondly the trace
(*.tr) and network animation file (*.nam) are generated, after running the simulations
in Ns-2.35. The first trace allows to distinguish all the events produced during the
simulation line by line for a comprehensive analysis of the network, and the second
trace represents the events in a graphical interface friendly for the user. Finally the
simulation results are filtered with awk.
In the two following tables the configuration parameters assumed for vehicular
traffic generation and network simulation respectively:
Table 1Parameters of traffic simulation for VanetMobiSim-1.1
Parameters Value
Simulation area
Number of nodes (vehicles)
Scenario
Number of lane
Number of traffic lights
Time interval between traffic light changes
Max velocity
Min velocity
Driver Model
Simulation time
1000 m × 1000 m
25, 35, 45, 55, 65,75,85,95
Urban Random
2
6
10000 ms
13.89 m/s
8.33 m/s
Intelligent Driven Model (IDM -LC)
3600s

Table 2 Parameters of network simulation for Ns-2.35
Parameters Value
Simulation area
MAC Type
N/W Interface Type
Interface Queue Type
Propagation model
Transmission range
Antenna model
Number of nodes (vehicles)
Number of connections
Routing protocols
Transport protocols
Traffic Type
Packet size
Transmission rate
Simulation time
1500 m × 1500 m
Mac/802_11
Phy/WirelessPhy
Queue/DropTail/PriQueue
TwoRayGround
250 m
OmniAntenna
25, 35, 45, 55, 65,75,85,95
12, 17, 22, 27, 32,37,42,47
DSDV, AODV, AOMDV
TCP
FTP
512 bytes
50 pack/s
60s
3.4. Performance metrics
Different performance metrics are used to check the performance of routing protocols
in various network environments. In our study we have selected packet delivery ratio,
average end-to-end delay and throughput for different number of vehicles in order to
check the performance of VANET routing protocols DSDV, AODV and AOMD
against each other.
3.4.1 Packet delivery ratio
The packet delivery ratio (PDR) is defined as the number of data packets that were
successfully delivered at destinations by the number of data packets that were sent by
sources [4]. This metric is calculated by dividing the number of packet received by
destination through the number packet originated from source [6]. The high packet
delivery ratio presents better performance of a protocol.
(%) (1)
Where Pr is total Packet received and Ps is the total Packet sent.
3.4.2 Average End to End delay (EED)
It is define as the calculation of the total time from the source end to the destination
end taken by the packet. For this metric, lower the time taken, more privileged is the
routing protocol [3].
The equation 2, is used to calculate the average delay from end to end.
[ms] (2)
Where i is packet identifier, n is number of packets successfully delivered, is
reception time and is send time.

3.4.3 Throughput
Throughput (TH) is defined as the number of the successfully delivered data packets
on a communication network. In different words it describes as the total number of
received packets at the destination out of total transmitted packets [4]. The high of
throughput presents better performance of a protocol. For this calculation has been
used the equation 3.
[Kbps] (3)
Where Br is received bits, T1 is start time and T2 is stop time.
4. SIMULATION RESULTS
We will compare three protocols DSDV, AODV and AOMDV under the above
simulation environment. The following graphs show the performance in simulation
based VANET environment with number of vehicles varying from 25 to 95 for
DSDV, AODV and AOMDV routing protocol, in terms of packet delivery ratio,
average end to end delay and throughput. The yellow, red and blue line shows graph
for DSDV, AODV and AOMDV routing protocol respectively.
Fig. 3 shows the graphs of packet delivery ratio. After number of nodes increased
by 5, the basic difference in the packet delivery ratio of both AODV and AOMDV is
less and always greater than 90%. Moreover, the AODV and AOMDV show high
packet delivery ratio compared to DSDV. But in case of DSDV, it gives the lowest
packet delivery ratio when the number of nodes is 65. So it is clearly shown that both
AODV and AOMDV outperformed DSDV in terms of packet delivery ratio.
Figure 3 Analysis of Packet Delivery Ratio
Fig. 4 shows the graph of average end to end delay. It is observed that initially and
finally average end to end delay of AODV is higher than AOMDV and DSDV. When
the numbers of nodes are 35 and 45, average end to end delay of both AODV and
AOMDV protocols are quite similar. When the number of nodes are 65, 75 and 85
average end to end delay of AOMDV is higher than AODV. But in case of DSDV, it
is giving lesser average end to end delay than AODV and AOMDV after number of

nodes increased by 5. So it is clearly shown that DSDV outperformed both AODV
and AOMDV in terms of average end to end delay.
Figure 4 Analysis of average End to End Delay
Fig. 5 shows the graph of throughput. It is observed that DSDV shows completely
higher throughput as compared to AOMDV and initially throughput of AODV is also
higher than AOMDV until number of nodes are 75. Up to 55 and 65 nodes the value
of throughput of three protocols DSDV, AODV and AOMDV is also sharply
decreasing from 441.88, 510.02 and 280.62 to 154.84, 160.86 and 119.31 (kbps)
respectively. Whereas AOMDV throughput is better than AODV after number of
nodes become 95.
Figure 5 Analysis of Throughput

5. CONCLUSION
In this paper, we simulated and analyzed the performance of three routing protocols
namely DSDV, AODV and AOMDV for vehicular ad hoc networks based on the
metric of packet delivery ratio, average end to end delay and throughput using Ns-2
and VanetMobiSim with number of vehicles varying from 25 to 95. After simulation
and analysis, it is concluded that performance of the both AODV and AOMDV
protocol are superior to DSDV protocols in packet delivery ratio. Moreover for higher
number of nodes the statistic of AODV packet delivery ratio is close to AOMDV.
However the end-to-end delay of DSDV is lesser than both AODV and AOMDV. In
addition, DSDV shows higher average of throughput as compared to AOMDV.
Another important finding was that simulation of different number of nodes only
marginally affected VANET routing performance in our experimental settings and
from these any single protocol is not suitable for efficient routing in different
environment. For VANET research area, routing protocol is always vital resource and
cope for further works; Therefore to this research, other new protocols can also be
studied.
6. ACKNOWLEDGMENT
I would like to thank all the anonymous reviewers for their constructive feedback on
the work presented over here which helped us successfully complete this paper. I
would like to thank Prof. Wang Dong for giving me the opportunity of working on
this research project.
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