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International Journal of Informative & Futuristic Research ISSN: 2347-1697

Volume 4 Issue 10 June 2017 www.ijifr.com

Abstract

In the last few years, Vehicular ad hoc networks (VANETs) have been quite a hot research area for the research community. Due to their unique characteristics such as high dynamic topology and predictable mobility, VANETs attract so much attention of both academia and industry. In this research work, an overview of the main aspects of VANETs from an Intelligent Transport Systems (ITS) research perspective is discussed. Research in the field of Intelligent Transport Systems (ITS) is emerging, motivated by the need for improved road safety and environmental concerns. To function properly, these applications require efficient routing protocols. However, existing mobile ad hoc network routing and forwarding approaches have limited performance in VANETs. This paper shows that routing protocols (like LAR and D-LAR) which account for VANET-specific characteristics in their designs, such as high density and

Simulation and modelling the performance

of Vehicular Communication for Intelligent

Transport Systems

Paper ID IJIFR/V4/ E10/ 033 Page No. 8010-8025 Subject Area Computer

Science

Key Words VANET, ITS, Routing Protocol, LAR, D-LAR, SBM method, Naya Raipur,

SUMO, NS-2

1st Neha Patel

M.Tech. Scholar,

Department of Computer Science,

School of Engineering & IT,

MATS University, Raipur-Chhattisgarh,India

2nd Deepak Kumar Xaxa

Assistant Professor,




3rd Devendra Kumar

M.Tech. Scholar,




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International Journal of Informative & Futuristic Research (IJIFR)

Volume - 4, Issue -10, June 2017

Continuous 46th Edition, Page No.: 8010-8025

Neha Patel, Deepak Kumar Xaxa, Devendra Kumar ::

Simulation and modelling the performance of Vehicular Communication for Intelligent Transport Systems

constrained mobility can provide good performance for a large spectrum of ITS applications. The main aspect and key concept for VANET simulations are a real world vehicular mobility model which will ensure conclusions drawn from simulation experiments will carry through to real world deployments. In this paper a tool called SUMO that allows users to easily generate real world mobility models for VANET simulations is considered. The real world city map like Naya Raipur cities drown using OpenStreetMap (OSM) which is a map of the real world and free to use under an open license. In experiment phase, intelligent transport system is implemented in Raipur city map and investigated the performance analysis of LAR and D-LAR routing protocol. Output of SUMO simulator is a real world mobility model and can be used by network simulator, NS-2. In this research work a Safety Message Broadcasting method (SBM) is proposed which forwards and notifies the vehicles about their speed and direction. The simulation results are obtained between SBM method, LAR and D-LAR protocol when nodes are moving according to a real world mobility model which is significantly different from that of the generally used random waypoint model at highway scenario. SBM method shows 6.16% in packet delivery ratio, 11.76% improvement in throughput, 6.09% improvement in average delay, 20.63% improvement in routing overhead and 15.74% improvement in normalized routing load as compared to D-LAR protocol.

I. INTRODUCTION

Wireless Communications in vehicular environments are operated by Intelligent

Transport Systems (ITS) for Vehicular Ad-Hoc Networks (VANETs). They are designed

and deployed with a motive to provide a consistent and secure environment for drivers by

cut down road accidents, traffic jams, and fuel consumption and so on. The car drivers

are notified about dangerous conditions by vehicle to vehicle (v-2-v) communications

and exchanging the messages about surrounding environments [1], [2]. The vehicular

networks are the advanced form of Mobile Ad hoc Networks (MANETS) and inherits

most of the characteristics such as high rate of topology change, high mobility , high

number of nodes and so on [1].[3]-[7].

An Intelligent Transport System (ITS) would be the future technology that plays a vital

role in solving real time accident and traffic jam conditions. An ITS is the advanced form

of Vehicular Ad Hoc networks which facilitates it by exchanging information among

vehicles in a precise manner with short dely. Furthermore, due to movement of vehicles

with varying speed in arbitrary direction makes the complexity for designing efficient

routing protocols. So far, Location added Routing (LAR) and its advanced form is

preferred for routing purpose in vehicular environment. Although, research in intelligent

transport systems is going over the world and quite very well implemented in USA and

European counties.

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In this paper, a smart way of broadcasting of message exchange among vehicles is

considered and a new method so called Smart Broadcasting & Modelling (SBM) method

is proposed. The research domain is vehicular ad hoc networks in which the latest trend

of research in Intelligent Transport System is studied. Initially, the proposed work also

studies the some basic routing protocol which is usually opted for routing in VANETs.

The incidence of congestion rises up the delay and packet loss (particularly for safety

messages) leading to alleviation of the VANETs’ routine [8]-[11]. The congestion be

able to be controlled in VANETs in diverse customs such as by modification the

transmission rate, modification the transmission power, shaping the contention window

size and prioritizing and scheduling the messages [13]-[22]. Moreover, congestion

control approaches in VANETs countenance some troubles which involves high

transmission delay, unfair resource usage, inefficient bandwidth usage, communication

overhead, and computing overheads, and so on [10], [13]-[22]. Therefore, a new

method is needed that would consider congestion problem and should be developed a

smart way of broadcasting of message to control delaying of messages that cause

congestion in network, particularly in serious situations where the safety messages be

supposed to be delivered without any significant delay and packet loss.

II. ARCHITECTURE OF VANETS

Figure 1 depicts three district domains of VANETs including In-vehicle domain,

Ad hoc domain, and infrastructure domain. In-vehicle domain is formed of OBUs.

Each vehicle is considered to be equipped with OBU. Short range wireless

communication is generated by OBUs for safety and non-safety communications. The

second domain is Ad hoc domain which is composed of OBUs and RSUs. OBUs

communications can be conducted by one-hop communication or multi-hop

communications that depend on the applications generating these communications

[24], [28]. The third domain is Infrastructure domain that is composed by RSUs and

Hotspots (HS). Infrastructure domain is employed to access the safety and non-safety

applications. RSUs provide internet access, and HS is considered for low

controlled environments. In the case that RSUs or HSs cannot provide internet access,

OBUs can employ integrated cellular networks including General packet radio service

(GPRS), Global System for Mobile Communications (GSM), Universal Mobile

Telecommunications System (UMTS), 4G, and WiMAX [24], [28].

Figure 1: VANET System Architecture [28]

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III. RELATED WORK

Routing has been a major research topic in MANETs. DSDV [30] and DSR [25] are

protocols that focus on the topology of the network to select the end-to-end

communication path. DSDV is a proactive protocol that may work well in small static

environments, but does not scale well in larger, dynamic environments in which link

information are frequently updated. RBVT-P is a proactive kind of routing protocol as

well, but unlike DSDV routing protocol it is not coupled to individual nodes. RBVT-P

creates a real-time outlook of the vehicular traffic on the roads. DSR is a source-based

routing that creates routes on-demand. The RBVT-R settles routes on-demand, but these

two routing protocols vary in the representation of the routes. In DSR routing protocol,

routes are series of nodes, thus leading to regular route break in VANETs, while in

RBVT-R, the routes are sequences of road intersections defining connected road

segments.

To pick up on traditional node-centric routing protocols that do not reflect on the road

topology, a hardly any protocols for VANETs [31, 32] take advantage of the fact that

movements of vehicles are constrained on roads to either predict the lifetime of routes in

node-centric protocols (and repair routes before they break) or reduce the number of

route breaks by selecting, during the route creation, neighbours moving in the same

direction and with a small relative speed. RBVT-R routing protocol vary from these

protocols in that the routes are road-based and their main mechanism are the road

intersections traversed on the path from source to destination.

Geographical routing protocols, such as GPSR [26], GFG [33], and GOAFR [34], use

node positions to route data between end-points. In static ad hoc networks, for which they

have been initially premeditated, they balance well because the only overhead is

generated by “hello” messages to keep informed the neighbour lists. However, under high

mobility VANETs, the recovery strategies proposed in the literature (when a forwarding

node cannot be found) are often based on planar graph traversals, which were shown not

to be as effective in VANETs due to radio obstacles, high node mobility, and the fact that

vehicle movements are constrained on roads, rather than being uniformly distributed

across a region [22].

The main concepts of anchor-based routing in sensor networks [35, 36] have been

adapted to vehicular networks environments. GSR [22] and SAR [37] integrate the road

topologies in routing using those concepts. In these routing protocols, a source node

calculates the shortest road based path from its current position to the destination. Similar

to RBVT, they include the list of intersections that defines the path from source to

destination in the header of each data packet sent by the source node. On the other hand,

[22], [37] do not think upon the real-time vehicular traffic, and as a result, they could

comprise empty roads or roads with network partitions. To alleviate this issue, A-STAR

[38] modifies GSR by giving preference to streets served by transit buses each time a

new intersection is to be added to the source route. The recently introduced CAR [23]

protocol finds connected paths between source and destination pairs considering real-time

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traffic. CAR uses “guards” added to “hello” messages to reflect the movements of the

source and destination nodes on the paths. Gytar [39] does not accumulate the full

intersection-based route in the packets. Instead, the selection of the next intersection is

made dynamically, each time choosing the next road segment with the best balance of

road density and road length.

MDDV [40] and VADD [41] use opportunistic forwarding to transport data from source

node to destination node. VADD uses historic data traffic flow to determine the best

route to the destination. MDDV considers the road traffic conditions as well as the

number of lanes on each road segment to select the best road-based trajectory to forward

data. In both routing protocols, whenever no vehicle node can be established by the

forwarding trajectory, a carry and-forward mechanism is used. The vehicle node which is

unable to transmit the data packet will store it until it finds a more suitable relay. These

protocols are well suited for delay tolerant applications i.e. applications for which the

users can tolerate a certain level of delay (up to a minute or more), as long as the data

eventually arrives. On the other hand, the RBVT routing protocols provide support for

applications that are not delay tolerant. RBVT protocols require that an end to end path

exists for data to reach the destination. Under very sparse vehicular traffic, as well as at

the early stages of the deployment of wireless technology in vehicles (while many

vehicles do not have wireless interfaces), opportunistic forwarding solutions, such as

these, will be needed for car-to-car ad hoc communications.

Note that real-life measurements with commercial GPS receivers [42] showed errors in

reporting of GPS positions in urban environment. Because RBVT protocols follow paths

made of road segments, they are more resilient to vehicle node positions errors of a few

meters. The integration of inertial navigation system to GPS receivers is expected to

improve the detection and handling of GPS position errors.

IV. PROBLEM IDENTIFICATION

The previous research is been discussed with Intelligent Transport System (ITS)

application in regards with vehicular ad hoc networks. As discussed in chapter 1 that ITS

application is future onwards application that would be utilized and ongoing research in

developed countries (like America, France, and Russia etc.). So, safety concern is

discussed to create communication among vehicles without any delay or collision. Also

the routing protocols performance is taken into account for a city traffic scenario.

Location aided routing (LAR) and directional location aided routing (D-LAR) protocols

are compared and simulated. The realistic environment is created by using SUMO

simulator and performance evaluation is done by using network Simulator 2. The

simulation was performed over three hundred vehicles and delay & network parameters

are considered. In the previous study, D-LAR performs better than the LAR protocol for city traffic

environment for VANETs and its enhancement is required. Both of them were compared

protocol on behalf of delay and hop count consideration. The author includes that future

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enhancement of D-LAR protocol is needed and it must be tested for other network

parameters too. As per ITS application is concerned, there could be improvement in a

routing protocol in city traffic environment for VANETs regarding location & speed of

vehicles. Also more parameters should be considered to contribute depth research, so

parameters more could be considered. Network congestion is not taken into consideration

since large scale city environment are characterized by high density of vehicles in

VANETs and their communication exchange may burden the wireless channel with high

traffic loads.

After formulation of problem identification phase, a new approach is proposed in this

paper called Smart Broadcasting and Modelling (SBM) method for vehicular

communication based on hop count analysis in ITS. In this method, a vehicle with status

update to transmit the data first listens to the channel. If the channel is ideal, the packet is

sent and if the channel is busy, the transmission is deferred for a random amount of ideal

channel time and then sent.

The proposed system formulates the VANET-ITS system model in which real world map

considered like city traffic road network (Naya Raipur) traffic environment. This would

help to find the best routes that maximize the Quality of Service (QoS) evaluated in terms

of connectivity, delay and packet delivery ratio. For Smart broadcasting of

communication packets, the proposed system implements broadcast function which

makes adaptive network exploration and integration of communication pairs and updates

the latest routing information along the routes.

V. PROPOSED METHODOLOGY

To support Intelligent Transport System applications, routing protocols of VANETs must

be able to efficiently transmit packets to related destinations. In order to cope with the

challenges described in previous chapter 3, we propose in this paper Digital Signature

based VANET-ITS architecture routing protocol performance analysis which would be

suitable for large-scale real world scenarios . One objective of these routing protocols is

to search the best QoS routing path which satisfies with different ITS applications

requirements based on real-time QoS of road side conditions & constraints expressed in

terms of namely connectivity probability, delay and packet delivery ratio. Besides, these

routing protocols are adaptive and scalable, and can effectively decrease redundant

overhead to cope with network congestion and limited bandwidth in VANETs.

Phase 1: The first objective to implement Safety Broadcasting and Modeling (SBM)

method, it is needed to form an intelligent transport system which is best suitable of

vehicular network architecture. A hypothesis is made that an ITS model would be

simulated using a real world map scenario and for this purpose a location of Naya Raipur

from Chhattisgarh is chosen. Here, the performance of LAR, D-LAR and SBM

mechanism routing performance would be analyzed for their better performance.

Phase 2: To implement SBM method a broadcast function is implemented in appropriate

files for network simulator 2. This function forwards the direction and speed of the

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vehicle. This function is timely broadcasted to other vehicles to be aware of each other

vehicles information about speed and their direction of moving.

Figure 2: SBM Phases

Phase 3: There is a unique method from which a real world map is actually been

simulated. For this purpose, a real world map location like naya Raipur from

Chhattisgarh is chosen in OpenstreetMap, and this map is extracted. Then this extracted

map is imported to Sumo simulator where many vehicles can be visualized and deployed.

In this set of experiment, number of vehicles ranges from 100 to 300 vehicles. Since the

primary objective of experiment is the analysis of routing protocols, so the traces of sumo

simulator is imported to network simulator 2 as mobility files for getting vehicles

movement.

Phase 4: In this phase, three routing protocols namely LAR, D-LAR and SBM are

analyzed and compared their routing performance when they are taken into consideration

for real world map scenario for naya Raipur from Chhattisgarh.

Phase 5: In the final phase, results obtained for routing protocols are plotted into a graph

to visualize the performance of LAR, D-LAR and SBM Mechanism. At this phase, it is

easily conclude that how much percentage improvement showed the SMB mechanism

over LAR and D-LAR method.

When a simulation scenario for an intelligent transport system for vehicular ad hoc

network is ready then vehicles need to broadcast a hello message for their status about

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their location. This process updates the routing table for the routing protocol. A source

vehicle node sends a data packet to the nearby neighbour vehicle about the status and

direction of moving using Smart Broadcasting and Modelling (SBM) method. This

method forwards the location and direction of vehicle as well as the speed of the vehicle

to neighbour vehicles for safety purpose so that no other vehicle comes with that lane on

which the source vehicle moving. The neighbour vehicles after receiving safety message,

forwards this message to other vehicles of the network for safety. If the safety message is

received successfully, they forward it and continue communication and finally a reply

function is invoked to reply the source vehicle that, a lane is clear to move forward and

safety messages is successfully delivered to the network. If the neighbour vehicles fail to

forward the safety message, it tries once to re-transmit the safety message, and then stop

the communication.

Figure 3: SBM Flowchart

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VI. RESULTS AND GRAPHS

In this paper, Naya Raipur city map is considered, instead of considering any random

map or grid map. Considered real map has been taken and processed using

OpenStreetMap (OSM). The map processing consists of embedding real time

environmental events like traffic on road and traffic signals. This processed map is

visualized using SUMO simulator GUI. Figure 4 shows extracted Naya Raipur City Map

in SUMO for VANET-ITS simulation. Figure 5 shows the view of Naya Raipur City

Map in a Sumo Simulator where the road side structure of a city traffic scenario could be

seen. Figure 5 shows the vehicles movements in a road structure obtained in SUMO

simulator. In this figure all the vehicles are moving with their ids shown. The vehicles are

deployed from 100 vehicles to 300 vehicles using SUMO simulator.

Figure 4: Snapshot of Naya Raipur City Map

Figure 5: SUMO view of Naya Raipur

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Figure 6 (a) shows the graph of throughput.

Figure 6: (a) Throughput

The Graph clearly shows that throughput is higher, in case of SBM method with Naya

Raipur highway scenario. It is increasing for all number of vehicles because the no. of

packets to be sent over the network is dropping over larger networks for all scenarios.

While in case of LAR and D-LAR protocol with Raipur highway scenario there is little

decrease in the throughput because the no. of vehicles are less managed over larger

network ranging from 100 to 300 vehicular nodes. The SBM method showed 11.76%

improvement than D-LAR routing protocol.

Figure 6 (b) shows the graph of Packet Delivery Ratio. The Graph clearly shows a

decrease in percentage of packet delivery ratio in case of both LAR and D-LAR routing

protocols.

Figure 6: (b) Packet Delivery Ratio

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It is sharply decreased after 100 nodes because the no. of nodes increased over the

network and there is much more nodes are sent with RREQ messages to find the required

destination node as the route is captured due to congestion in the network. Hence, graph

shows that SBM method performs well under all scenarios compared to LAR and D-LAR

protocols. The SBM method showed 6.16% improvement than D-LAR routing protocol.

Figure 6 (c) shows the graph of End to End Delay.

Figure 6: (c) End to End Delay

The Graph clearly shows an increase in percentage of end to end delay in case of both

LAR and D-LAR routing protocols. It is increasing because the no. of packets has to send

over the network which is increasing the no. of vehicle nodes with next to next scenario.

Hence, LAR and D-LAR not performs well under urban scenario larger network

compared to SBM method under NAYA RAIPUR City urban scenario. Therefore, End to

End Delay graph shows that LAR and D-LAR protocol is much more affected as there is

very big difference in the output for all scenarios than SBM method based routing

protocol. The SBM method showed 6.09% improvement than D-LAR routing protocol.

Figure 6 (d) shows the graph of Normalized Routing Load.

Figure 6: (d) Normalized Routing Load

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The Graph clearly shows that delay is quite similar in all cases i.e. LAR, D-LAR and

SBM method up to 300 nodes. This is due to the nature of internal performance of

routing protocols that it gives the fake reply to the neighbour’s vehicles that it is the part

of the network. There is increase in the NRL after 100 nodes because the no. of vehicles

nodes increases in the topology from 100 to 300. Therefore, NRL graph shows that both

protocols are little affected as there is small difference in the output for all scenarios. The

SBM method showed 15.74% improvement than D-LAR routing protocol.

Figure 6 (e) shows the routing overhead for SBM method, LAR and D-LAR protocols.

The graph shows the gradually increase in routing overhead since the number of route

request and route send packets increase as the number of vehicles increase to

communicate with each other. Overall, SBM method has lower routing overhead than

LAR and D-LAR routing protocols.

Figure 6 (e): Routing Overhead

This chapter outlined performance constraints and metrics for the SBM, LAR and D-

LAR protocols being investigated in this study. The set of experiments are then

introduced and the relative performance of the protocols under each usage scenario is

explained. This chapter provided a comparison of the performance of each protocol under

different traffic loads. The results of the comparisons have highlighted the best

performance of SBM method than LAR and D-LAR protocol for all scenarios. The SBM

method showed 20.63% improvement than D-LAR routing protocol.

VII. CONCLUSION AND FUTURE WORK

After formulation of problem identification phase, a new approach is proposed in this

paper called Smart Broadcasting and Modelling (SBM) method for vehicular

communication based on hop count analysis in ITS. In this method, a vehicle with status

update to transmit the data first listens to the channel. If the channel is ideal, the packet is

sent and if the channel is busy, the transmission is deferred for a random amount of ideal

channel time and then sent. The proposed system formulates the VANET-ITS system

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model in which real world map considered like city traffic road network (Naya Raipur)

traffic environment. This would help to find the best routes that maximize the Quality of

Service (QoS) evaluated in terms of connectivity, delay and packet delivery ratio. For

Smart broadcasting of communication packets, the proposed system implements

broadcast function which makes adaptive network exploration and integration of

communication pairs and updates the latest routing information along the routes.

To simulate real world map traffic scenario, the proposed method uses the

OpenStreetMap to choose the metro city environment. This trace is then imported to

SUMO simulator and then the performance f routing protocols is tested in Network

Simulator 2. The SBM method is compared with D-LAR and LAR protocols to evaluate

the routing performance by considering related traffic information, vehicle distribution,

communication range, channel transmission rate, road length and so on. The parameters

for performance considered are: End to End Delay, Packet Delivery Ratio, Packet Loss

Ratio, NRL and Throughput.

There is considerable concern regarding reliability of messages and subsequent

evaluation for revocation. So this work can be further extended for checking reliability of

messages as well as design of parameters for an efficient certificate revocation procedure

in a VANET based Intelligent Transport Systems. Furthermore bigger and more complex

topologies are on the way in order to cover more realistic VANET scenarios. Further plan

is going to investigate more Position-based Algorithms and implement into NS-2 as well

as to testing into realistic VANET scenarios.

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ISSN: 2347-1697






PAPER CITATION

Patel, N., Xaxa, K.D., Kumar, D. ( (2017) :: “Simulation and modelling the

performance of Vehicular Communication for Intelligent Transport Systems” International Journal of Informative & Futuristic Research (ISSN: 2347-1697),

Vol. (4) No. (10), June 2017, pp. 8010-8025, Paper ID: IJIFR/V4/E10/033.

Available online through- http://www.ijifr.com/searchjournal.aspx

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