PERFORMANCE ANALYSIS OF ROUTING PROTOCOLS WITH ROADSIDE UNIT INFRASTRUCTURE IN A VEHICULAR AD HOC NETWORK

International Journal of Computer Networks & Communications (IJCNC) Vol.12, No.4, July 2020
DOI: 10.5121/ijcnc.2020.12402 19
PERFORMANCE ANALYSIS OF
ROUTING PROTOCOLS WITH ROADSIDE
UNIT INFRASTRUCTURE IN A VEHICULAR
AD HOC NETWORK
Safae Smiri, Abdelali Boushaba, Rachid Ben Abbou and Azeddine Zahi
Intelligent Systems and Applications Laboratory (LSIA), Faculty of Science and
Technology, Sidi Mohamed Ben Abdelah University, Fez, Morocco.
ABSTRACT
Vehicular ad-hoc networks (VANETs) represent a powerful and active field of research and have given rise
to many challenges related to routing protocols and communication problems with other vehicles or fixed
infrastructure called roadside units (RSU). The dynamic topology and the obstacles encountered in VANET
environments mean that the routing of data and the communication between vehicles is confronted with
many problems, and particularly in vehicular applications that require reliable communication and
satisfactory quality of service (QoS). This paper promotes the intention of infrastructure in an urban
scenario and studies the performance of routing protocols considering the constraint of mobility. This
leads us to analyze a wide range of routing protocols to ensure optimal coverage and continuous
connectivity, taking into consideration two types of data traffic in realistic environments that depend on
certain performance metrics. The paper also investigates which protocols provide better performance with
RSUs by ranking the results for QoS.
KEYWORDS
VANET, Intelligent Transportation System (ITS); Routing protocols, Roadside unit (RSU), Urban topology,
NS-2, VanetMobiSim, Quality of service (QoS).
1. INTRODUCTION
Over the last decade, intelligent transportation systems (ITSs) [1] have aimed to increase our
knowledge of traffic and mobility management by using information technologies and
communication for sustainable development in a quickly evolving world. Vehicular ad-hoc
networks (VANETs) [2] represent a domain of ITS that offers several innovative, reliable and
cost-effective applications that can be used in a wide range of services, from safety applications
to entertainment for drivers and passengers (internet access, etc.). Due to these applications,
advances in communications have played a major role in VANETs [3]. This has allowed the
deployment of three different architectures (Figure 1), including hardware and software structures
that provide communication between vehicles (V2V), offering flexible and less expensive
communication. In this strategy, the vehicles can communicate directly without infrastructure or
any installation on roads. However, due to the highly dynamic mobility involved, the network is
faced with frequent disconnection. Communication between vehicles and infrastructure or
roadside units (RSUs) (V2I/V2R) is, therefore based on a communication system using RSU
infrastructure or a base station installed at the edge of the road. The RSUs are connected via a
wireless or wired interface. The use of RSUs has the advantage of providing users with services

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relating to internet access, road traffic and exchanging data between the car, garage or home, for
remote diagnostics. Another option is hybrid communication (V2V and V2I), which combines
two communication modes (V2V and V2I) in order to achieve effective communication. Many
factors need to be taken into account in order to meet the requirements for deploying different
types of vehicular applications [4], [5] or VANETs. The network connectivity with/without the
use of an RSU varies according to the density of the VANET environment; a high density allows
the network to be connected, while a low density has a longer transmission delay and high
communication failures. In addition, the Quality Of Service (QoS) requirements for real-time
applications include the end-to-end delay and packet transmission rate. For these reasons, the
design of an efficient routing protocol that meets all the requirements of a VANET is considered
a major challenge. Thus, improving reliability and reducing interference of the system in
VANET, need a promising routing protocol which should be evaluated using the standard IEEE
802.11p. There are several survey studies that compare routing protocols in VANETs, but the
majority compare only a small selection of protocols and consider only a limited number of
performance criteria and metrics, without taking into account the presence of RSUs. The
comparison and perception is not relevant and always remain to be discovered by the user. For
this reason, the deployment of infrastructure such as RSUs is insufficient in VANETs.
The main goal of this survey is to contribute a better comparison between a variety of known
routing protocols from different categories, involving RSUs and two types of traffic in an urban
topology. This kind of study can significantly affect daily life, and its requirements motivate our
interest. Our choice to study the environment mentioned above arises from the problems faced in
terms of communication [4] due to the high mobility, dynamic topology and scalability of a
VANET. Moreover, the density of the network varies, including very dense networks in urban
areas where communication is interrupted, leading to many conflicts in communication, and there
are therefore numerous problems to address. The aim of our comparative study is to select and
examine a variety of protocols that can support communication between vehicles and RSUs in a
complicated and highly dynamic environment, such as in a VANET. Thus, our review provides
researchers with the ability to choose the most relevant and promising protocol for a routing
strategy, depending on the communication with RSUs and to achieve a particular QoS.
The remaining of this paper is organized as follows. In Section 2, we review seven possible
protocols, and in Section 3, we discuss related works, describing the most popular studies of
VANETs. In Section 4, we pay particular attention to communication with RSUs by carrying
outa performance evaluation of a realistic mobility model for a VANET. Our performance
measures are described in Section 5, while Section 6 presents the experimental results and an
analysis. Finally, the conclusion and future works for researchers are presented in Section 7 and
8.
Figure 1. VANET architecture: (a) vehicle-to-vehicle communication (V2V); (b) vehicle-to-infrastructure
or RSU communication (V2I/V2R); (c)hybrid communication ( V2I and V2V)

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2. OVERVIEW OF ROUTING PROTOCOLS
In the following paragraphs, we discuss the operating mechanism of routing protocols, the cons
and the pros of each one. All protocols are listed with their main advantages and disadvantages in
Table 1.
2.1. Topology-based routing protocols
The topology-based routing category uses the link information from the routing table to transmit
data from the source to the destination. We will present in the next three classifications of this
category.
2.1.1. Proactive routing protocol
An optimized link-state (OLSR) [6] is an optimized link-state routing protocol. It provides the
routes available during the route request due to its proactive nature. Each node exchange
topology information’s by defining its neighborhood-based on one and two hops, using HELLO
messages. From its neighbouring nodes (one hop), it chooses a set of multi-point relays (MPRs)
to reach all neighbours at the second hop. OLSR generates three control messages (HELLO,
topology control (TC) and multiple interface declaration (MID) messages) to maintain the routing
tables, as shown in Figure 2.
Multipath dynamic address routing (MDART) [7] is an advanced extension of the DART
protocol [8], which uses the choice of the shortest path in order to respond to changes in
topology. It guarantees the transmission of data in several ways, without generating additional
communication costs, based on the routing information stored for each node. The discovery of
the road and all available routes to the destination in MDART also involve no additional cost.
2.1.2. Reactive routing protocols (on demand)
The principle of a reactive protocol is to establish a route on-demand. When a node wishes to
transmit a packet, it makes a route request and searches for a path until it arrives at the
destination. In our work, we will discuss the AODV, AOMDV and DSR protocols in more detail.
A reactive scheme is illustrated in Figure 3.
Ad-hoc on-demand distance vector (AODV) [9] is a protocol that uses an on-demand
algorithm from Bellman-Ford. When a source node wants to send a packet, it determines an end-
to-end route to a destination. The AODV protocol has two well-defined mechanisms: discovery
of routes, and maintenance of routes. Route discovery occurs when there is no route to the
destination, while route maintenance is responsible for maintaining the route between the source
and the destination. The reactive protocol AODV is shown to be suitable for both high and low
densities of vehicles in [10], [11].

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Figure 2. Operating mechanism of protocol OLSR using Multipoint Relays (MPRs)
Table 1 : Pros and Cons of routing protocols
Protocol Classification Pros Cons
AODV Reactive Updates route to the destination
the use of sequence numbers lead to
eliminate the routing loop
Reduces overloading and processing
of memory
Has a mechanism in case of route
failure
Causes significant delay due
to the route discovery
process
Induces an inconsistency in
the route
Produces heavy overload
due to control messages
Consumes additional
bandwidth
OLSR Proactive Suitable for high-density networks
Reduces transmission delay of packets
Supports real-time applications
Causes congestion in the
network due to frequent
sending of control packets
DSR Reactive Includes the routes in the header of the
packets, which eliminates routing
loops
Uses caching when a new route is
discovered
Decreases performance due
to mobility
Causes delay and additional
packet loss in the network
ZRP Hybrid Designed for large-scale networks
Uses the reactive inter-zone approach
to handle the delay in the network
Highly dynamic topologies
are not supported
The size of the zone is
predefined and cannot be
modified
MDART Proactive Uses multiple routes between source
and destination to handle topology
changes
Provides protection against road
failure by dividing traffic into a set of
disjoint paths
Produces a high number of
control packets in high-
mobility networks
AOMDV Reactive Provides effective fault tolerance in a
dynamic network
Manages the charge in the network
and avoids the possibility of
congestion
Maintains connectivity
Induces an increase in
message charges during
route discovery due to
flooding of multiple-node
RREQ messages
GPSR Geographical Uses greedy forwarding technique to
transmit packets
Suitable for scalability and evolving
networks
Ineffective without GPS
device
Performance degradation
with high mobility

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Ad hoc on-demand multipath routing (AOMDV)[12] is an improvement to the protocol
AODV that allows for the discovery of several routes between the source and destination. It
guarantees a route without a loop, based on sequence numbers. The maintained paths correspond
to the maximum value of the sequence number to the destination, and all information about the
next hop is kept for the destination. The route discovery process is restarted if all paths fail.
Dynamic source routing (DSR) [13] was designed for ad-hoc multi-hop networks, and forms
routes when a source node wants to send a packet to the destination. In addition, it uses the
concept of source routing. The two-path mechanisms of AODV are applied in DSR, and each
node maintains a cache of routes containing the route leading to the destination nodes.
Figure 3. Operating mechanism of Reactive protocol
2.1.3.Hybrid routing protocols
The zone routing protocol (ZRP) [14] was one of the first hybrid protocols used in large-scale
networks [15]. Route discovery is performed by a limited number of route searches, using inter-
one and intra-zone routing to provide route discovery and route maintenance (see Figure 4).
Using reactive routing performed by the inter-zone routing protocol (IERP), which keeps nodes
within the zone, it makes a single route request that can result in multiple route responses without
overloading resources or loop problems. Proactive routing uses the intra-zone routing protocol
(IARP), which updates the status of the network and maintains routes to nodes outside of the
routing area. As a result, reactive routing reduces the network overhead and manages the delay
caused by reactive routing.
2.2.Geographic routing protocols
Greedy perimeter stateless routing (GPSR) [16] based on the geographical position obtained
using a positioning system such as GPS. When transmitting packets, each vehicle periodically
broadcasts beacon packets to its direct neighbors, and maintains a list containing its own position,
the position of its destination and the position of its direct neighbors (one hop), as shown in
Figure 5.

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Figure 4. Operating mechanism of hybrid protocol ZRP
Figure 5. An exemplary of GPSR functionality: (a) Greedy process and greedy failure
(b) perimeter process Right hand Rule

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It uses two methods of packet transmission. Greedy forwarding is the first strategy, and this is
applied to choose the next optimal vehicle (next hop) that will take over the routing, by selecting
the nearest neighbor that is closest to the destination. However, if the transmitter node is a shorter
distance from the destination than all its neighbors, the second strategy of perimeter forwarding is
applied. This involves using the right-hand rule by routing around the perimeter until a node
close to the destination is reached. We assume in our work that the source knows the
geographical location of the destination.
3. RELATED WORKS
The high mobility and instability of vehicles pose new challenges in VANETs. All routing
protocols and perceptions of research aim to enhance the QoS in terms of the packet delivery
ratio (PDR), transmission delay and network overhead. However, it is difficult to choose a
specific routing protocol that works effectively in all VANET environments. One of the most
important surveys was presented in [15]. The authors presented a robust study of VANET
dissemination and a specific discussion of performance and QoS requirements. They then carried
out a classification and comparison of broadcast protocols by selecting several performance
metrics such as the delay, PDR, overhead, throughput, scalability, and network reachability. The
authors acknowledged that the mobility of the nodes, frequent topology changes and breaks that
characterize VANETs make dissemination a major problem as a research topic. In this context,
they discussed the main issues that a researcher may be faced with by examining future
challenges and trends that could take advantage of the most effective mechanisms available. They
also pointed out that despite existing work, there is still a need for QoS development and
optimization, since these studies are based on performance criteria set by researchers according to
their topics of interest. The authors of [17] presented a survey of routing mechanisms based on
geographical protocols. They classified the different protocols into two categories, namely
infrastructure-based and infrastructure-less, the latter of which was classified into basic and
advanced routing protocols. In addition, the authors provided an analysis of VANET
architectures and various VANET applications. They then presented a comparative study that
took into consideration different parameters and variants of greedy forwarding to transmit
packets using V2V and V2I approaches. The majority of protocols used GPSR as the base
protocol in all simulation scenarios, and the authors suggest that the evaluation of protocols
should be performed in these environments. In this context, numerous works have shown many
motivations requirements based on the geographic information of vehicles in a VANET. In
summary, the overall goal of the various authors of these surveys is to help engineers and
researchers to improve vehicle network applications for driver safety and comfort.
Many works have also been dedicated to comparing the performance of routing protocols,
considering various performance metrics and parameters such as mobility models. The authors of
[18] presented one of these studies, and compared the performance of two protocols OLSR and
AODV in urban road scenarios, based on two roads and several intersections. Four metrics are
considered: the PDR, the overhead, the throughput, and the E2E delay. The authors used CBR for
the data traffic in the two density variation scenarios over transmission ranges of 250 and 500 m.
The results showed that the routing costs and delays in both protocols increased with density. It
was therefore concluded that the AODV and OLSR protocols are impractical for a VANET with
a high density of vehicles. In the same context, the authors of [19] presented a comparative study
of the AODV, OLSR and DSR protocols in urban and highway scenarios, in terms of the PDR
and E2E delay. Their goals were to achieve robust and easy communication between vehicles for
driver safety. The AODV protocol performed well in terms of PDR as function of the density
variation. Another study involving a performance evaluation of routing protocols adapted for
VANET was presented by the authors of [20]. They evaluated the impacts of the speed and
density of vehicles using various metrics. The AODV, AOMDV, DSR, ZRP, DSDV and OLSR

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protocols were simulated using the NS2.35 and SUMO simulator with a CBR data traffic model
and various numbers of nodes in a VANET and a MANET. The simulation results showed that
the AODV protocol achieved good performance in terms of delay and other performance metrics,
unlike in [19], where OLSR outperformed AODV in terms of the E2E delay. The authors
concluded that the applicability of MANET routing protocols to a VANET is unsatisfactory, due
to the high mobility and low node density. The performance results presented in all these studies
provide an adequate overview of the applicability of routing protocols and data integrity to
VANETs, and thus could help in designing improvements to the existing protocols.
The studies discussed above [18]–[20] evaluate the performance of VANET networks by
considering only the V2V communication mode and CBR data traffic. In contrast, other studies
have processed communications using RSU and TCP data traffic. In this context, the authors
of[21] present QoS studies of the AODV and DSDV protocols using the two communication
modes of V2V and V2I for different RSU relay placements in urban scenarios, based on CBR
data traffic. The performance of AODV in all scenarios was better than that of DSDV in terms of
the sending, receiving and forwarding throughput and the data loss. The authors observed that the
scenario using a strategy with RSUs placed on both sides of the road provided better performance
and hence better data transmission. The researchers in [22] analyzed the AODV protocol with a
new data transmission scheme for communicating with enhanced RSU. The purpose of this new
data transmission scheme was to discover routes in order to reduce overhead and improve QoS.
The results showed that the proposed method improved significantly the performance compared
to AODV protocol, in terms of the PDR and overhead. The authors of [23] considered two types
of data traffics in an urban environment depending on certain metrics. Their analysis of various
routing protocols addressed many of the problems of V2V communication and will be consistent
with future simulation environments for VANETs. The researchers in [24] used TCP with CBR
data traffic to evaluate the AOMDV protocol in terms of the PDR, E2E delay, packet loss ratio
and throughput. The AOMDV protocol was designed to efficiently transmit data with respect to
the AODV protocol in a VANET network. The multipath AOMDV protocol minimized the delay
and packet loss ratio and maximized the PDR, while enhancing the throughput. To our
knowledge, no attempt has been made to study and evaluate the performance of RSUs with TCP
and CBR traffic, in an urban environment; this is a problem of interest for VANETs, since it
involves many problems and complications that need to be addressed.
The motivation for carrying out this survey is to bring forth an up-to-date global summary of
routing protocols in VANETs, and a performance evaluation of an enormous range of a routing
mechanism. Unlike other surveys, our work evaluates and compares the most popular and
efficient routing protocols with significant description. To the best of our knowledge, there is a
lack of simulation studies or comprehensive research that evaluates and compares routing
protocols using IEEE 802.11p technology. Thus, a study of the impact of varying data traffic
conditions while exchanging information with RSUs is required. This paper aims is to describe
and analyze the performance of seven popular and important routing protocols considering RSUs
in an urban area with two types of data traffic and different QoS performance metrics. This
analysis can be useful for researches and engineers when developing practical applications and
when selecting the most appropriate routing protocols while satisfying the constraints of VANET
networks.

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4. PERFORMANCE EVALUATION
4.1. Model of mobility
The vehicle mobility model has been widely used in the literature, due to its ability to provide an
accurate model for VANET nodes. According to the authors of [25], the integration of a mobility
model can produce significant results. In our work, we use the VanetMobiSim [26] generator, as
it provides a high level of realism in our simulation scenarios. Mobility generators can be
classified into two types: macroscopic and microscopic. The macroscopic model captures the
traffic conditions that influence vehicular traffic, for example the characteristics of a road (one or
two-ways, speed, and numbers of lanes), the topology of the road network, traffic lights at
intersections and signs, etc. Although this type of simulation is more complex, it is very useful
and is necessary when studying the interactions of vehicles with infrastructure. Following
[27],we select the mobility model, Intelligent Driver Model with Lane Change model (IDM-LC),
which takes into account traffic lights, intersections, vehicle speeds and lane changes, and is
therefore the most convenient for our work. Table3 shows the various parameters used on the
experiment evaluation in VANET.
4.2. Parameters of scenarios
In our simulation, we compare different ad hoc routing protocols in an urban environment using
the NS-2 network simulator depending on the type of traffic required by the user (voice, data or
video). Which are the file transfer protocol FTP/TCP and the constant bit rate protocol
CBR/UDP. A random graph of streets is generated by VanetMobiSim, with a variable number of
vehicles and a topology network with nine RSUs. In order to increase the success rate for packet
delivery and decrease the average delay, we use IEEE802.11p, which is suitable for a VANET.
The main simulation parameters and network characteristics describing the scenario are presented
in Table 2. The macroscopic and microscopic mobility model parameters are presented in Tables
3 and 4 [28].
Table 2: Values of the different parameters used in the simulation
Parameters used for traffic model Value
Background traffic CBR/UDP
FTP/TCP
Number of connections 10,15,20,25,30,35,40
Packet size 512 packets
Packet rate 8 packets/s
Simulation time 300 s
Simulation parameters and network characteristics
Simulator version NS-2.35
MAC & PHY layer protocols IEEE 802.11p
Transmission range 250 m
Propagation model Two-ray ground
Type of antenna OmniAntenna
Parameters used for mobility model
Dimensions of the simulation area 1000 x 1000 m²
Number of vehicles 50 vehicles
Mobility model IDM-LC
Traffic direction Multidirectional

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Table 3: Parameters of the microscopic mobility model
Parameter Description Value
I Length of vehicles 5 m
A Maximum acceleration 0.6 m/s²
B Deceleration 0.5 m/s²
Ath Threshold of acceleration 0.2 m/s²
S0 Jam distance 2 m
T Safety distance 1.5 s
P Politeness 0.5 s
minstay Min stay duration of node 5 s
maxstay Max stay duration of node 30 s
Table 4: Parameters of the macroscopic mobility model
Clusters Obstacles by
100 x 100 m²
Clusters in the
simulation zone
(%)
cluster density
(1000x1000m²)
Speed
(km/h)
Downtown 2 10 4 60
Residential 5 40 4 40
Suburban 1 50 4 100
5. PERFORMANCE MEASURES
PDR is the ratio between the total number of packets received and those sent by the source. This
metric reveals the reliability and efficiency of the protocol in terms of guaranteeing the delivery
of packets. The following equation is used to calculate the PDR:
End-to-end delay (E2E or EED) is the average time taken by the data packets between the
source and the destination. E2E is a metric that needs to be improved with the shortest delay. It is
also important in security-related applications. The following equation is used to calculate E2E:
Packet delay variation (jitter) is the average difference between the delays of twosuccessive
packets (X and Y) received by a node and belonging to the same data stream. It is calculated as
follows:

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RoutingCost is the amount of information in the network required to receive a packet of data. It
is calculated based on the number of bytes for routing packets, including the transmission of
routing packets and control packets, divided by the sum of the number of received data packets.It
is calculated as follows:
Efficiency it is an important metrics to show the amount of routing packets sent efficiently to the
target. It is calculated as follows:
6. EXPERIMENTAL RESULTS
6.1.1. Measurement of PDR
In this section, we study the PDR for CBR/TCP data traffic with RSUs. The traffic load increases
due to the high probability of collisions, and therefore, the number of delivered packets
decreases. In a simple scenario where a node wants to generate a packet, the routing protocol will
find a route to the destination via the discovery mechanism. However, if the MAC layer is unable
to transfer a packet because there are no alternative nodes, the packet will be lost.
Figures 6a and 6b show that the best results are obtained with the reactive protocols (AODV and
AOMDV), since these have the capacity to maintain the route when sending data. From the same
figure, we can see that the use of RSUs leads to a higher PDR for the routing protocol in Figure
6b than in Figure 6a. A lower rate is seen for the DSR protocol in the scenario without RSUs,
since as mentioned in Section 2; it is unable to repair broken links locally. Better performance is
achieved for communication between RSUs and vehicles for a low number of CBR connections.
DSR uses an alternative route, as it can store more than one path in the cache. In addition, the
GPSR protocol achieves better performance than the other two protocols, due to its routing
method, which involves finding the neighbour with the lowest distance to the destination and
accurate location information, which is an important factor in achieving a high PDR. The
proactive protocol MDART achieves a lower performance than the reactive protocols in both
scenarios (with and without RSUs), as the congestion caused by broadcasting RREQ packets may
lead to loss of packets. OLSR is the best option, since it can reduce the retransmission of data
packets and maintain the best possible path, thus reducing the congestion and the overload.
MDART achieved the weakest results, showing a significant decline and then stabilization as a
function of CBR connections. In scenarios with RSUs, the proactive protocols obtained a higher
PDR than in scenarios without RSUs. The OLSR protocol achieved 85% for a low number of
connections, and 49% for 40 connections, while the hybrid protocol ZRP decreased progressively
in both scenarios and is an inefficient choice for a highly dynamic topology such as a VANET.
From Figure 6c and 6d, we have the best results are those for the reactive protocols AODV,
AOMDV and DSR in the scenario using RSUs. This is due to their capacity to build routing

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information and to maintain a route when it is required to send data. The DSR protocol gives the
best performance, as it can store more than one path in the cache. All routing protocols perform
well, with a rate greater than 97% for all numbers of TCP connections. As mentioned in Section
4, the TCP ensure the data delivery from the source to the destination. Thus, the performance of
the different routing protocols in both scenarios is effective. The use of RSUs with TCP traffic
provides good performance and a generally high connection load, and the rate exceeds 98% for
the geographic protocol GPSR, the proactive protocols OLSR, MDART, the reactive protocols
AODV, AOMDV, DSR and the hybrid ZRP protocol. The scenario without RSUs gives low
performance for the OLSR, AODV, and ZRP protocols compared to the other protocols in the
same scenario. The communication between vehicles and RSUs therefore achieves good
performance using TCP data traffic, because it is easier to send a packet to a fixed target such as
an RSU than a moving destination. In addition, the more coverage areas increase in the network,
the number of vehicles and RSUs will communicate with each other and the possibility of one
vehicle being in the coverage area of another is high. Hence, the transmission of packets from the
source to the destination will be reliable.
6.1.2. Measurement of delay
The total delay includes the delays caused by buffering during transmission at the MAC layer,
congestion and route discovery. In fact, the packets generated by the vehicles are not all sent to
their destinations. For that, the vehicles put them in the queue. Thus, the performance of each
protocol is generated based on its own strategy. As shown in Figure7a and b, the position-based
routing protocol GPSR performs better than the reactive protocol DSR and the hybrid protocol
ZRP. The effectiveness of GPSR in different traffic scenarios can be explained by its use of
neighbour nodes in the next-hop forwarding node. This minimizes the number of hops, hence the
time taken to transmit the packet to the target node is reduced. All routing protocols exhibit good
performance in both scenarios. We can see that GPSR is the most efficient option in the scenario
with RSUs. The reactive protocols achieve better performance in the scenario with RSUs than
without, and give better discovered quickly with the presence of RSUs along the route. The
proactive protocol OLSR produces a relatively low delay, while the opposite is true for the DSR
and ZRP protocols.
As shown in Figure 8a and b, the routing protocols perform well in both the V2V and V2R
communication scenarios in terms of the E2E delay, except for the case of GPSR; this gives a
longer delay, since when a decision is made, the vehicle traffic pattern is not considered. Besides,
the reactive protocol DSR has a relatively high data delivery delay due to its reactive nature.
Regarding the performance of the other protocols with the two modes of communication, we note
that the proactive protocols OLSR and MDART, the reactive protocols AODV and AOMDV and
the hybrid protocol ZRP perform better than the other mechanisms. These protocols seem to be
stable and perform well, with a delay that varies from 15 to 25 ms, as shown in Figure 8a. When
RSUs are added, there is unexpected variation between protocols depending on the variation in
the TCP data traffic load. AODV, AOMDV, OLSR, MDART and ZRP give good performance
with an increase of the TCP connection load. Consequently, these results are better than the
remaining schemes. A VANET network consists of vehicles, which act as nodes. These nodes
may fail whenever due to software faults and hardware tampering, and this leads to the
generation of faulty nodes in the system.

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Figure 6. Packet Delivery Ratio: (a) as function of CBR data traffic load without RSU (b) as function of
CBR data traffic load with RSU (c) as function of TCP data traffic load without RSU (d) as function of
TCP data traffic load with RSU.
If a vehicle sends data to a vehicle that is faulty at the time of routing, then the data may be
dropped and anomalies are obtained. The DSR protocol uses more than one route to transfer data
packets from the source node to the destination node, and this causes delay as it does not always
use the shortest path to deliver data packets from the source node to the destination node. In
DSR, the nodes store the source routes in their caches. When new routes are learned by the
nodes, the entries in the cache are updated for these new routes. These anomalies may be because
DSR maintains a route cache.

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Figure 7. Delay: (a) as function of CBR data traffic load without RSU (b) as function of CBR data traffic
load with RSU
Figure 8. Delay: (a) as function of TCP data traffic load without RSU (b) as function of TCP data traffic
load with RSU

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6.1.3. Measurement of jitter
Figure 9 shows the results for the performance of the routing protocols in terms of jitter, which
are very similar to those obtained for the E2E delay. The simulated protocols are the most
efficient in the scenario with RSUs. We note that the position-based protocol GPSR is the most
efficient, and achieves a low data delivery jitter for low CBR data traffic loads. Nevertheless, it
isn't meaningful due to its PDR. It should be noted that the majority of protocols show stable
performance (except for DSR, ZRP and AODV) with high numbers of connections without
RSUs. However, when the CBR load on the network is greater than 20 connections, the hybrid
protocol ZRP and the reactive protocol DSR give low results in the scenario with RSUs
compared to the geographical protocol. In ZRP, the delay is incurred by the IERP and IARP
methods.
We note from Figure 9c and d that all of the protocols give better performance for both modes of
communication compared to the CBR connection. The packet delivery delay of the position-
based protocol GPSR is influenced by the TCP data traffic load. GPSR gives poor results
compared to DSR in both scenarios. The position of the neighbor node is very likely to change,
meaning that the next hop is very likely to move out of communication range, and the delay is
then slightly longer. The DSR and AODV protocols give poor performance compared to the
proactive protocols and the ZRP hybrid protocol in the scenario with RSUs. The alternation of
the values obtained and the intersection between the curves can be explained by the behavior of
each protocol in the network the changes in the topology of network over time and the presence
of obstacles, which causes the breaking of links. This leads to degrading the performance a
function of data traffic load.
Figure 9. Jitter: (a) as function of CBR data traffic load without RSU (b) as function of CBR data traffic
load with RSU (c) as function of TCP data traffic load without RSU (d) as function of TCP data traffic load
with RSU

34
6.1.4. Measurement of routing cost
The routing cost is represented by the ratio between the number of transmitted routing packets
and the number of data packets received. At the beginning of this article, we make clear a
VANETs as a dynamic networks where vehicles exchange information via wireless links. If we
fix the number of nodes, the routing cost decreases as we increase the number of CBR and TCP
connections.
The routing costs for the seven protocols for both modes of communication as a function of CBR
data traffic load are shown in Figure 10a and b. The routing costs for the various protocols
remain almost stable for the two scenarios, since if we increase the number of CBR connections
between nodes, the number of control packets remains almost the same. The routing protocols in
the scenario with RSUs have a cost that is lower than 35 packets. GPSR, AODV, AOMDV,
MDART and OLSR have low overheads, since they do not generate additional RREQ and RREP
packets in the network. DSR has the highest cost in both scenarios, followed by the ZRP hybrid
protocol.
The impact of the routing cost in the different protocols a function of the variation in the number
of TCP connections is illustrated in Figures 11a and b. The number of control packets decreases
as the number of connections between nodes and RSUs increases. The best performance is
obtained by the GPSR protocol with V2V and V2R communication. A performance evaluation
shows that the routing costs in GPSR, OLSR and AOMDV in a network with RSUs are low, and
are constant for varying numbers of TCP connections compared with other protocols. The highest
values are seen for the DSR reactive protocol and the ZRP hybrid protocol. As mentioned in
Section 2, DSR and ZRP are ineffective and rapidly change their topology in a high-mobility
network such as a VANET.
Reactive routing protocols such as AODV also suffer when the network is flooded with traffic, at
startup time or if there are high levels of traffic between the majority of the nodes in the network.
If any other metric than the minimum hop is used, there will be large amounts of overhead traffic.
Furthermore, the vehicles in each network are randomly distributed over a real environment in a
rectangular distribution, and any relationship failure along the path of the source to reach the
target; therefore, we have greater probability of route disconnection when route is long than short
ones. The scalability is limited due to a important factors. In fact, in small areas, the need for
flooding each RREQ across the network due to the low number of vehicles. Nevertheless, as the
network grows, the entire network must be flooded each time a route needs to be discovered by
each network node.
6.1.5. Measurement of efficiency
Figure 12a and b show the efficiency of different routing protocols with variation in the CBR
data traffic load. The geographical protocol GPSR achieves a rate higher than 80% with the use
of RSUs as a function of the CBR connections. It shows a gradual increase as the number of CBR
connections increases. MDART, OLSR and AOMDV also perform well with increasing numbers
of connections between nodes and RSUs. The efficiency of the protocols mentioned above
becomes almost stable, with a rate greater than 50%. The reactive protocol AOMDV exceeds
50% while MDART, GPSR and OLSR reach an efficiency higher than 75% for 30–40
connections. Moreover, they outperform DSR, AODV and ZRP in both scenarios.
In terms of efficiency a function of TCP connections, Figure 12c and d show that the
geographical protocol GPSR performs best both with and without RSUs. It achieves a rate of
90%, which remains stable for varying numbers of connections. This allows us to conclude that

35
GPSR is efficient in dense and dynamic networks. AOMDV and OLSR achieve stable levels of
efficiency and better rates than MDART and AODV. AODV shows an increase in efficiency as
the traffic increases except for DSR and ZRP, the performance of these protocols reaches a rate
of higher than 88% in the scenario with RSUs, and then stabilizes for high numbers of TCP
connections.
Figure 10. Routing Cost: (a) as function of CBR data traffic load without RSU (b) as function of CBR data
traffic load with RSU
Figure 11. Routing Cost: (a) as function of TCP data traffic load without RSU (b) as function of TCP data

36
Figure 12. Efficiency: (a) as function of CBR data traffic load without RSU (b) as function of CBR data
traffic load with RSU (c) as function of TCP data traffic load without RSU (d) as function of TCP data
7. DISCUSSION
Our study presents several important results concerning the evaluation of different routing
protocols, in order to analyze the problems encounter in VANETs. Through this study, we can
deduce that the use of roadside infrastructure has a strong effect in terms of the QoS compared
with communication without infrastructure. We studied an urban environment using RSUs, and
summarize our analysis in Table5, which exhibits that the optimum results with regard to
minimizing the number of control messages and ensuring the transmission of packets are
achieved by the geographic protocol GPSR, for both types of traffic. Adding RSUs to the
network allows vehicles to use these fixed infrastructures as they travel along a road, and the use
of geographical position gives rise to good performance. However, the use of RSUs degrades the
performance for some reactive and proactive protocols. Due to the differences in the mechanism
of operation from one protocol to another. The addition of RSUs also generates additional control
messages in the network, since the presence of RSUs during the transmission of a data packet
requires the generation of several control messages by both the vehicles and the RSUs. As a
result, the performance in terms of efficiency will be influenced, since the efficiency depends on
the number of control messages (see Section5). It is clear from the results shown in Table 5 that
the DSR protocol generates a high routing cost, which causes degradation of the efficiency.

37
Table 5: Comparison of Seven Routing Protocols Studied in the Urban environment
Efficiency
TCPUDP
HigherHighest
ModerateModerate
LowestAverage
HigherModerate
ModerateHighest
LowLowest
HighestHigher
RoutingCost
TCPUDP
ModerateLow
LowLowest
HigherHigher
LowLeast
ModerateLow
Average
Moderate
ModerateLowest
Jitter
TCPUDP
Low
Moderate
LowestLeast
AverageHigher
ModerateLow
ModerateAverage
LowAverage
AverageLow
Delay
TCPUDP
LowestHighest
ModerateLow
ModerateLow
AverageHigher
ModerateLowest
ModerateAverage
AverageModerate
PDR
TCPUDP
Moderate
Moderate
HigherHighest
HigherLeast
Moderate
Moderate
HigherLowest
AverageAverage
ModerateHigher
Protocols
AODV
AODMV
DSR
OLSR
MDART
ZRP
GPSR

38
The DSR and GPSR protocols incur significant delays for CBR and TCP connection loads, due to
high vehicle speeds and loss data packets. The vehicles can therefore be very far apart, leading to
long delays. These observations allowed us to realize the importance of routing messages using
RSUs along the way. In the concrete case of an urban environment, vehicles tend to drive at
different speeds and are faced with several obstacles; they should therefore be able to change the
route for each CBR and TCP connection.
8. CONCLUSIONS
This paper presents a comprehensive research of the various categories of routing protocols in
VANET networks, and describes a simulation model based on two types of data traffics. A wide
variety of routing protocols are compared in realistic environments under different conditions in
terms of their QoS. In view of the problems and difficulties encountered in VANET networks, we
studied the response of these routing protocols for V2R communication, using RSU fixed
infrastructures and V2V communications. The aim of this work is to provide researchers and
designers with a better analysis and comparison in order to support the QoS and to give an
interesting and practical reference for future works. Based on the analysis of the results, it can be
deduced that the use of RSUs has improved the performance of routing protocols compared to
communication without infrastructure. The location-based protocol performs well compared to
other protocols in both environments. Proactive protocols give better results in terms of time and
jitter, due to their proactive natures. In addition, we found that reactive protocols performed well
in terms of PDR, routing cost and efficiency, compared to the hybrid ZRP protocol, except for
the DSR protocol, which showed performance degradation for some simulation cases. In
perspective, we will be moving towards an improvement to geographical versions with other
types of traffic and other simulation environments.
CONFLICTS OF INTEREST
The authors declare no conflict of interest.
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