Evaluation The Performance of MAODV and AODV Protocols In VANETs Models

M. A. Al-Shabi
International Journal of Computer Science and Security (IJCSS), Volume (14) : Issue (1) : 2020 1
Evaluation The Performance of MAODV and AODV
Protocols In VANETs Models
M. A. Al-Shabi mshaby@taibahu.edu.sa
Department of Management Information System,
College of Business Administration,
Taibah University, Saudi Arabia
Abstract
This paper to study, analyse the performance of multicast technology using the MAODV
(Multicast On-demand Distance Vector Routing Protocol) in the VANETs (Vehicle Ad-Hoc
Networks), this protocol using widely in MANETs (Mobile Ad-Hoc Network). The wireless nodes
in the wireless vehicle networks are the same wireless devices, which are integrated with a
sensor and designed specifically for the design of safety, privacy and security applications.
Researchers are interested in developing and enhancing the number of service quality
parameters (packets received, delay, productivity, node power consumption, etc.). The aim of this
paper is to introduce and optimize VANETS multi-cast transmission technology to reduce delay,
increase throughput and reduce packet loss. Although, presents an analytical study of the
Enhanced Protocol (MAODV) Protocol (AODV) and compares it to AODV performance in
VANETs.
Keywords: Wireless Network(VANETS), AODV Protocol, MAODV Protocol.
1. INTRODUCTION
The vehicle industry is developing day by day with new technologies, such as electronic
intelligence and smart communication devices, to make road use more comfortable and secure.
One of the developments that vehicle companies have begun to use is the idea of integrating
wireless communications with vehicles for greater convenience for road users as well as security
through a new technology called VANETs. VANETs are component of MANETs (Mobile AdHoc
Networks), which implies that each node can move freely and remain linked within the network
coverage. The nodes are mobile in VANETs and MANETs. However, the mobility of VANETs is
restricted to roadside infrastructure, while the motion of MANETs in nature is more random.
VANET nodes are extremely mobile and have adequate rechargeable battery energy to
synchronize to rapid topology modifications. In this technique, each vehicle will be equipped with
a wireless connection to enable vehicles to communicate with each other, in addition to
communication towers on both sides of the road to connect remote vehicles to each other or to
connect to the Internet, and even connect trains and aircraft on this network, making the volume
of information exchange is very large as Figure 1 . the Previous studies present in related work
section focus on studying, analyzing and improving protocols and routing algorithms that will limit
packet loss, delay and energy consumption by node.
The aim of this paper is to apply multichannel transmission technology and optimize its use in
VANETs in order to reduce delay, increase throughput and reduce packet loss.
Improving the performance of these networks is the most important objective of this research. We
have to study, analyze and employ new routing techniques in VANETs and traffic accidents have
a significant role in the death of a large number of people, prompting efforts in developed
countries and vehicle manufacturers to find solutions to ensure road safety. Vehicle
manufacturers are competing to equip their vehicles with the latest technology to increase road
safety. These technologies range from Global Position System(GPS) to Events Data Recorder

M. A. Al-Shabi
(EDR) named as (black box), night vision devices, light and rain sensors to navigation, which is
the latest vehicle technology or what is known as computers on wheels [1] .
FIGURE 1: VANETs Wireless Network.
With the development of wireless networking technologies and their use in various aspects of life.
The researches has been developed to develop wireless technology that enables vehicles to
communicate with each other to exchange information and mitigate traffic accidents VANETs,
However, the exchange of information is between mobile vehicles together or between mobile
vehicles and fixed roadside units providing road information or Internet access services.
The rest of the paper is organized in eight sections. Section2 presents related work. Section 3
illustrates the classification of Routing protocols in VANETs. In section 4 we present criteria to
choosing a routing protocol in VANETs. Section 5 present the Mobility models in VANETs. In
section 6 shown the many scenarios are implement in different mobility models. Section 7 present
the results and discussion simulation methodology and comparison the performance of AODV
and MAODV protocols using the simulation results. Finally section 8 concludes the work.
2. RELATED WORK
More than one previous study has analyzed the performance of routing protocols in VANETs,
because of the importance of these networks and their increasing use. Some studied the
performance of MANTs when used in wireless network such as [2], which evaluated the routing
protocols for wireless mobile networks when used in VANETs using the OPNET simulator for the
most appropriate protocols within this type of network, Consistently, AODV,DSR,TORA protocols
were studied. Similarly, Study [3] compared AODV, DSR and DSDV routing protocols when used
in wireless vehicle networks for throughput and with packet size change. This study shows that
DSR has better performance in this type of network. The study also indicates that these protocols
are ineffective when used in wireless vehicle networks on highways, It increases the routing load
over the network and reduces the data packet delivery rate and the average delay due to
interruptions in lanes due to high vehicle speed. Study in [4 ] compared AODV and DSR with
routing protocols for wireless vehicle networks.

M. A. Al-Shabi
This study showed that AODV and DSR protocols reduce network performance compared to
protocols for wireless vehicle networks.
The study in [5] compared AODV, AOMDV, OLSR, DSR and GSR protocols for packet delivery
and average delay and indicated that AODV is the best and can be used in vehicle networks. In
[6] this study compared the routing protocols AODV, DSDV, and OLSR, this study indicated that
the AODV protocol is best for its ability to maintain pathways between nodes by means of
information exchanged between nodes, DSDV suffers from routing over the network.
Study [7] proposed position-based routing protocol named (Anchor Based Street and Traffic
Aware), and showed that this protocol increases the rate of packets and reduces the delay.
The study [8] proposed position-based protocols called Greedy Perimeter Stateless Routing,
which needed geographic information on the nodes closest to the target to pass data packets,
this protocol has some problems in large cities because it relies on direct communication.
3. ROUTING PROTOCOLS IN VANETS NETWORKS
Routing protocols in VANETs are classified into two basic classes[9]:
1. Topology Based Routing Protocols
2. Position Based Routing Protocols
There are many routing protocols that can be used in both VANETs and MANETs such as AODV,
DSR, TORA and proactive routing protocols such as OLSR. We will analyze AODV, MAODV
routing protocols in VANETs.
3.1 Ad-Hoc On-demand Distance Vector (AODV)
It is an interactive routing protocol where paths are detected between nodes on demand, it
includes a mechanism to detect and maintain the path[10].
Path detection mechanism :
The path is detected by sending a path exploration Route Request(REQ) from source node and
the source node is waiting to receive the path exploration Route Replay(RREP) from the
destination, If the source node does not receive a response within a specified period of time, it
assumes that no path is available. When a path exploration request reaches the specified target,
the path information will be passed using the unicast to the source node for the specified
node[11] When a source node sends route request to its neighbors, it will either receive a
response from its neighbors if it has a route for the target, or these adjacent nodes will send the
request back to its neighbors with the node count increases. If a nodes receives multiple track
requests, if it receives a request with the same Broadcast ID as an earlier request, it will ignore
the duplicate request in order to maintain free communication with loops[11].
When the request message reaches the target, the target node responds to the request, if the
request is automatically returned, the reverse path will be routed towards the source node and
retain the path of all intermediate nodes where the reverse path is established. Each node
maintains the path within the routing table for a defined period ACTIVE_ROUTE_TIMEOUT, such
as figure 2.

M. A. Al-Shabi
FIGURE 2: AODV Route Discovery.
3.2 Multicast On-demand Distance Vector Routing (MAODV)
Developed by the University of California, it is an extended interactive routing protocol for the
AODV protocol that supports multicast[12-15]. In this protocol each group of nodes has an
address and the node you want to send data to this group is sent to the address of the group or
any node within the group to reach data to all the nodes combine the group.
Each group of nodes is organized using a tree structure, consisting of group members and a
number of routers. Each group of nodes has a leader and the first node to join the group is the
leader of this group, in the case of several members, one member is elected as the group leader
through a set of periodic messages Group Hello(GRPH). Each group has its own serial number
that increases periodically to reflect the novelty of the group, if more than one path is available for
the group, the node that wants to send to the group chooses the path with the largest serial
number, if the serial number is equal, the path in which the number of hops is less is chosen.
Each node in the network can send multicast data to the group and if the source node is not a
tree member and has a group path in the unicast route table it sends the unicast data to a group
member [16].
How is a node joined to the group?
Figure 3 shows that the new node that want to join sends a RREQ message to all adjacent
nodes and waits for the RREP message to confirm the join to the group with a MACT message
and builds the entry within the ’Multicast Route Table as a group member.
FIGURE 3: A Node Joins The Group In The MAODV Protocol.

M. A. Al-Shabi
Multicast Activation(MACT): The message that the node sends to activate joining the group, If the
node not receive an RREP message, the node assumes that this group does not exist and
identifies itself as the leader of the group. For leaving group: Any node that wants to leave the
group sends a MACT(pure) message to the group leader and becomes out of the group.
4. CHOOSING THE ROUTING PROTOCOL IN VANETS NETWORKS
When choosing a routing protocol it must meet several requirements:
1. The number of control messages and routing messages is too small to affect the narrow
bandwidth.
2. Ability to detect multi-hop path
3. Ability to maintain the path and discover new paths
4. Avoid routing loops
4.1 Challenges Facing VANETs
There are several challenges in VANETs:
- The Significant change in network topology: Routing protocol performance in VANETS
networks varies depending on the chosen mobility model.
- Propagation model: In VANETs, the propagation model in space is not the same.
- Integrated sensors: Routing protocols provide useful routing information such as vehicle
speed and position information.
4.2 VanetMobiSim Simulation
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[ 17].
The VanetMobiSim simulator is used to simulate the movement of vehicles connected to each
other with VANET wireless networks[18]. This emulator is written in JAVA and is open source[24].
This emulator generates files to simulate network node traffic in formats compatible with several
network emulators such as NS2,Qualnet.
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)” describing
perfectly car-to-car and intersection managements and Support for traffic lights at intersections
(TrafficLight).
5. MOBILITY MODELS IN VANETS
Wireless vehicle traffic is simulated using mobility models that have a significant impact on the
performance of these networks. Popular models:
5.1 Intelligent Driving Model with Intersection Management (IDM_IM)
IDM_IM mobility model is a macroscopic car-following model that adapts a vehicle speed
according to other vehicles driving ahead. in The IDM_IM mobility model nodes movement
depends on the neighboring nodes movements. In particular, IDM-IM models two different
intersection scenarios: a crossroad regulated by stop signs, or a road junction ruled by traffic
lights [19].
5.2 Intelligent Driver Model with Lane Changing (IDM_LC)
This model extends IDM-IM model, it allows vehicles to change lane and overtake each
other’s. This model takes into account the movement of the vehicle, its speed and the
surrounding environment, For example, when the speed of the front vehicle decreases, the next
vehicle should slow down [20].

M. A. Al-Shabi
5.3 Traffic Lights Model
Similar to the IDM-LC model, it supports multiple paths, route change mechanism, and simulation
of terminal intersections and traffic lights.
6. THE SIMULATION
We will use the NS-2 network simulator and embed the MAODV source code in [21]. To analyze
the performance of interactive routing protocols (AODV, MAODV) for VANETs using (IDM-IM),
(IDM-LC), (Traffic Light). Three files are generated using the VanetMobiSim simulator for each
model from the previous models and include these three files that simulate wireless vehicles in
the NS-2 simulator. more than one scenario we be will using:
6.1 Scenarios with IDM_LC Model
This simulation with five nodes sent and several receiving nodes, table 1 shows the parameters
environment for simulation.
Simulation Parameters
Routing Protocols AODV,MAODV
Mobility model IDM_LC
Simulation time 900 sec
Number of cars(senders) 5
Number of cars (receivers) 10,20,30,40
Simulation area X=1000 m, Y=1000 m
Speed Max=20.00 Min=15.00 m/sec
Pause time 0.0
Traffic type CBR
Packet size 512 Byte
Rate 5 packets/sec
TABLE 1: 5 Nodes Sent and Several Receiving In IDM_LM.
(a) (b)
FIGURE 4: (a) Packets Delivery Ratio in IDM_LC Model with 5 nodes, (b) Average End to End Delay in
IDM_LC Model with 5 nodes.
The second scenario with 10 nodes sent and several receiving nodes, table 2 shows the
parameters environment for simulation.
Mobility model IDM_LC
10 20 30 4010 20 30 40

M. A. Al-Shabi
Pause time 0.0
Traffic type CBR
Rate 5 packets/sec
TABLE 2: 10 Nodes Sent and Several Receiving In IDM_LM.
(a)
(b)
FIGURE 5: (a) Packets Delivery Ratio in IDM_LC Model with 10 nodes, (b) Average End to End Delay in
IDM_LC Model with 10 nodes.
6.2 Scenarios with IDM_IM Model
This simulation with five nodes sent and several receiving nodes, table 3 shows the parameters
Mobility model IDM_IM
Pause time 0.0
Traffic type CBR
Rate 5 packets/sec
TABLE 3: 5 Nodes Sent and Several Receiving In IDM_IM.
10 20 30 40
10 20 30 40

M. A. Al-Shabi
(a)
(b)
FIGURE 6: (a) Packets Delivery Ratio in IDM_LM Model with 5 nodes, (b) Average End to End Delay in
IDM_LM Model with 5 nodes.
The second scenario in IDM_IM with 10 nodes sent and several receiving nodes, table 4 shows
the parameters environment for simulation.
Mobility model IDM_IM
Pause time 0.0
Traffic type CBR
Rate 5 packets/sec
TABLE 4: 10 Nodes Sent and Several Receiving In IDM_IM.
(a) (b)
FIGURE 7: (a) Packets Delivery Ratio in IDM_LM Model with 10 nodes, (b) Average End to End Delay in
IDM_LM Model with 10 nodes.
6.3 Scenarios with Traffic Light Model
This first simulation with 5 nodes sent and several receiving nodes, table 5 shows the parameters

M. A. Al-Shabi
Mobility model Traffic Light
Pause time 0.0
Traffic type CBR
Rate 5 packets/sec
TABLE 5: 5 Nodes Sent and Several Receiving In Traffic Light.
(a) Light (b)
FIGURE 8: (a) Packets Delivery Ratio in traffic light Model with 5 nodes, (b) Average End to End Delay in
traffic light Model with 5 nodes.
The second scenario in Traffic Light with 10 nodes sent and several receiving nodes, table 6
shows the parameters environment for simulation.
Mobility model Traffic Light
Pause time 0.0
Traffic type CBR
Rate 5 packets/sec
TABLE 6: 10 Nodes Sent and Several Receiving In Traffic Light.

M. A. Al-Shabi
(a) (b)
FIGURE 9: (a) Packets Delivery Ratio in traffic light Model with 10 nodes, (b) Average End to End Delay in
traffic light Model with 10 nodes.
7. RESULTS AND DISCUSSION
From the results in all scenarios in all figures (4-9) and with the three mobility models, the delivery
rate of packets using MAODV is better than that of packets using AODV. Because the MAODV
protocol sends all packets from the source node to the target in a Unicast way, while the MAODV
protocol sends packets in a multicast way, by transmitting to the group address where all nodes
within the group have the group address and receive the data packets.
From the results, in all scenarios in all figures (4-9) and in the three different mobility models, the
average packet delay when using AODV is lower than the average packet delay when using
AODV. Because the MAODV protocol sends the data packet to one of the group members that it
publishes to the rest of the group members, the delay is less than the transmission of all packets
from the source node to the target node, as well as using the AODV protocol which needs to
detect the path of the nodes sent to the target node.
8. CONCLUSIONS
In this paper we evaluate the efficiency i.e. the performances of both (AODV and MAOVD)
Protocols. The performance metrics such as packet delivery ratio (PDR), throughput, average
end-to-end delay and normalized routing load are evaluated using NS-2. The realistic vehicular
mobility traces are generated using Intelligent Driving Model with Intersection Management
(IDM_IM) , IDM_IC and traffic light models , based tool VanetMobiSim. These two protocols were
tested by varying constant bit rate (CBR) against various metrics. It is concluded that MAODV
outperforms AODV when packet delivery ratio is concerned. Even then MAODV protocol is more
suitable for highly VANET networks where network partitioning and route failure occur very
frequently because of its capability to determine multiple routes but at the cost of additional
overheads involved for route discovery. Therefore we can say that MAODV routing protocol is
more efficient than AODV routing protocol for VANET networks.
For the future studies, we recommend the following:
- Study the impact of site-based routing protocols, and protocols that depends on topology
together.
- development of protocols for the network of vehicles supports multicasting and
broadcasting for all Vehicles.
- Develop mobility model so that it is as close as possible to reality.
- Development of the improved algorithms and technologies in MANETs to VANETs.

M. A. Al-Shabi
9. REFERENCES
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