SECURE DATA DISSEMINATION SCHEME FOR VEHICULAR AD …

SECURE DATA DISSEMINATION SCHEME FOR

VEHICULAR AD-HOC NETWORK

Aneel Rahim

38-FBAS/PHDCS/S08

Submitted in partial fulfillment of the requirements for the degree of Doctor of

Philosophy in Computer Science at the Faculty of Basic and Applied Sciences

International Islamic University,

Islamabad

Prof. Dr. Muhammad Sher May, 2011

Approval

Aneel Rahim 38-FBAS/PHDCS/S08 ii

APPROVAL

Title of Thesis: Secure Data Dissemination Scheme for

Vehicular Ad-hoc Network

Name of Student: Aneel Rahim

Registration No: 38FBAS/PHDCS/S08

Accepted by the Department of Computer Science, INTERNATIONAL

ISLAMIC UNIVERSITY, ISLAMABAD, in partial fulfillment of the requirements

for the degree of Doctor of Philosophy in Computer Science.

Viva Voce Committee

Prof. Dr. Muhammad Riaz

Dean, Faculty of Basic and Applied Sciences

International Islamic University, Islamabad

Prof. Dr. Muhammad Sher (Supervisor)

Chairman, Department of Computer Science


Dr. Muhammad Zubair (Internal Examiner)

Department of Computer Science


Dr. Muhammad Abdul Qadir (External Examiner-I)

Dean, Faculty of Engineering and Applied Sciences

Mohammad Ali Jinnah University, Islamabad

Dr. Sajjad Mohsin (External Examiner-II)

Dean, Faculty of Sciences and Information Technology

COMSATS Institute of Information Technology, Islamabad

Wednesday, 25th

May, 2011

Abstract

Aneel Rahim 38-FBAS/PHDCS/S08 iii

Acknowledgements

Aneel Rahim 38-FBAS/PHDCS/S08 iii

ACKNOWLEDGEMENTS

First thanks to Allah and my parents for giving me the ability and confidence to

complete this task on time.

I would like to express my sincere gratitude to my supervisor, Prof. Dr. Muhammad

Sher without whom this thesis would not have been possible.

Special thanks to my friends whose love give me direction to achieve this goal.

Research Achievements

Aneel Rahim 38-FBAS/PHDCS/S08 v

RESEARCH ACHIEVEMENTS

• More than 26 publications in International conferences and journals with total

impact factor equal to 10.15.

• Research idea is presented in Doctoral Symposium on Research in Computer

Science”, IEEE, Lahore, 9-10 Aug 2008.

• Perform one and half year research work in Prince Muqrin Chair for IT

Security King Saud University

• Reviewer of 5 international journals

• Technical Program Committee Member of 12 international conferences.

Journal Editor

1. Special Issue “Wireless and Network Security”,

Telecommunication Systems, Springer, Impact Factor 0.396

2. Special Issue “Secure Multimedia communication in Vehicular adhoc

networks”, Multimedia Tools and Applications, Springer, Impact Factor 0.462

3. Special Issue “Security and Enrichment of Multimedia Services, Information,

An International Journal, Impact Factor 0.09

Workshop Chair

4. First International Workshop on Wireless and Network Security (WNS 2010),

In Conjunction with 4th International Conference on Information Security and

Assurance (ISA 2010) Sheraton Grande Ocean Resort, in Miyazaki, Japan.

5. Session chair in SechTech 2010, Bali, Indonesia.

List of Figures

Aneel Rahim 38-FBAS/PHDCS/S08 vi

List of Figures

Aneel Rahim 38-FBAS/PHDCS/S08 vii

List of Figures

Aneel Rahim 38-FBAS/PHDCS/S08 viii

List of Tables

Aneel Rahim 38-FBAS/PHDCS/S08 ix

LIST OF TABLES

Table 2.1: Comparison of Broadcast Protocols for VANETs………..……………...28

Table 4.1: Simulation Parameters…....………………...…………………...………..46

Table 4.2: Simulation Parameters. ………………………………......………...….…52

Table 6.1: Simulation Parameters.....…………………………...………...………….70

Table 6.2: Simulation Parameters .………………………………...…………...........74

Table 7.1: Simulation Parameters .……………………………...………………...…89

Table of Contents

Aneel Rahim 38-FBAS/PHDCS/S08 x

Table of Contents

Aneel Rahim 38-FBAS/PHDCS/S08 xi

Table of Contents

Aneel Rahim 38-FBAS/PHDCS/S08 xii

Table of Contents

Aneel Rahim 38-FBAS/PHDCS/S08 xiii

Chapter #1 Introduction

Aneel Rahim 38-FBAS/PHDCS/S08 1

CHAPTER #1

INTRODUCTION



1. Introduction

This chapter covers the characteristics of mobile and vehicular adhoc networks.

Simulators like NS2, CARISMA, and EvalVid are briefly explained in this section.

Current research project in the field of VANETs is also described.

1.1 Mobile Adhoc Networks

Mobile Ad Hoc Network (MANET) is a temporary network without any

infrastructure, base station and router. They share information with each other through

single and multihop wireless nodes [1]. Several features of the MANETs [2] are

described below.

i) Dynamic Topologies:

Communication in adhoc network is directly or through intermediate nodes. So

dynamic network topology will affect the performance of network as node joins and

leaves the network rapidly.

ii) Bandwidth Constraints:

Wired networks have more bandwidth as compared to wireless network. Several

constraints like noisy channel and interference affect the network.

iii) Energy Constraints:

It is a main constraint in MANETs as all nodes dependent on limited battery.

Different factors exist that affect the nodes communication just because of low battery

time.

iv) Limited Physical Security:

Security attacks are easily launched on the wireless network as compared to any

other network. Several security threats exist like malicious node attack, Dos attack,

jamming, traffic analysis, rogue access points, fake positioning and packet sniffing.



1.2 Classification

Communication in adhoc network has no fixed categorization. Information sharing

can be done in single hop or if the node is far away then information is forwarded

through the intermediate node to the destination [3]. There is no centralized server or

dedicated router for multimedia communication in the vehicular adhoc networks.

Single hop and multihop scenario can be easily understandable with help of figure1.1.

Figure 1.1: Classifications of MANETs

Singlehop

Multihop







1.6 Simulators

Simulators are used to analyze the performance of unicast, multicast and broadcast

protocols [13] in the VANETs. Following are the simulators that are commonly used

for the research purpose.

i) Network Simulator

It is used to evaluate the performance of wired and wireless protocols and measure

the throughput, delay, packet loss etc. in vehicular environment [14]. It is written in

C++ and run on Linux and Windows platform (with help of Cygwin [15]).

ii) EvalVid

Jirka Klaue proposed a framework “EvalVid” [16] to measure the quality of video

being transferred in wired and wireless network. With the help of it, PSNR, packet

delay, jitter and packet loss of multimedia traffic [17] [18] can be determine.

iii) CORSIM

Microscopic Traffic Simulation Model (CORSIM) has both functionality of

freeway and street simulation. Several characteristics of CORSIM [19] are described

below.

• Simulate large amount of network traffic

• Multiple programs can run simultaneously

• Low error rate



iv) GrooveSim

GrooveSim [20] has the following features.

• Geographic simulator for routing in VANETs

• Easy to use

• Simulates large number of vehicles

• Mainly used for inter vehicular communication

v) SWANS++

• It is the extension of wireless simulator [21]

• Simulates the VANETs scenario

• Provides the graphical interface

vi) CARISMA

• It is developed by BMW Group Forschung and Technik,

• Written in C++.

• Based on the Krauss-model

They are also certain limitation of CARISMA [22].

• Suitable for smaller simulation scenarios.

• Vehicles do not overtake each other.

• No Traffic signs

• Multiple lanes in each road direction are not available

• No sense of packet collision

• Hidden node effect is not considered



vii) AppSim Simulator

It works together with the CARISMA and provides the graphical user interface

and visualizes the simulation. It is written in Java and developed by the BMW

research group.

viii) TraNS

• Network and Traffic simulator [23].

• Graphical user interface.

• Specially designed for vehicular environment.

• Open source.

1.7 VANETs Research Projects

Several research projects (Roadnav, CarTalk, COMCAR, SeVeCom, EPFL

Vehicular Networks Security Project etc) are in progress in the VANETs. We will

discuss few of them, which are mentioned below.

i) Roadnav

Main characteristics of Roadnav project [24] is given below.

• United States Street map generation

• Vehicle position can be determined

• Graphical interface

• User friendly

• Compatible with Linux and Window platform



ii) CarTalk

CarTALK 2000 is sponsored by EU and core idea is to facilitate driver safety with

the help of inter vehicle communication. A vehicle initiates a message to alert the

driver when there is some danger situation [25].

iii) COMCAR

• Focuses on the multimedia services [26] in VANETs.

• German Ministry for Education and Research sponsors this project.

• Provides IP services for mobile communication.

iv) Car2Car

Car2Car communication project [27] has the following features.

• Enhances European standard for vehicle to vehicle communication.

• Builds up realistic operation policy.

• Checks the feasibility of car2car communication in real work.

• Wireless standards are developed.

v) SeVeCom (Secure Vehicular Communication)

• It is funded by European Union.

• Main focus is on security in the VANETs application.

• Security design and implementation.

• It provides privacy.

• It provides authentication.

• Handles security threats and attacks.

• Enhances the Safety applications [28].



vi) eSafety

• Development of road safety

• Reduces the accidents

• Sponsored by European Union [29].

vii) EPFL Vehicular Networks Security Project

Vehicular Networks Security Project provides the following features for vehicular

communication, are discussed below [30].

• Privacy

• Revocation & trust

• Authentication

• Handle security threats

• Reduces the effect of security attacks

• Develops Trans simulator for VANETs environment

viii) Network on Wheels

• German research plan.

• Originated by BMW AG.

• Started in 2004.

• Solves technical problems on data security.

• Enhances communication protocols for car-to-car communications [31].



1.8 Routing Protocols

In this section, we shall discuss the existing proactive, reactive protocols and

describe the Ad hoc On Demand Distance Vector and OLSR protocols in detail.

1.8.1 Reactive Protocols

Reactive protocols [32] are on-demand protocols, which find a path only on

request. Dynamic Source Routing protocol and Ad hoc On Demand Distance Vector

protocol are the examples of reactive protocol. These protocols use simple flooding to

establish a route. When node get route request, there is no information present at that

time so it is very useful to measure the delay.

Ad Hoc on Demand Distance Vector Protocol (AODV)

• Reactive routing protocol

• Minimizes the number of broadcasts

• Creates demand routes

• Proposed for ad hoc network

• No memory constraints

• Low processing [33].

1.8.2 Proactive Protocols

It is table based protocols [34], which automatically checks the connection if finds

then forwards the message to it. Examples are

• Destination-Sequenced Distance Vector protocol

• Wireless Routing Protocol



• Temporally-Ordered Routing Algorithm

• Lightweight Mobile Routing Protocol.

The Optimized Link State Routing Protocol

RFC3626 [35] explains the working of OLSR. Following are the features of

OLSR [36].

• Designed especially for MANETs

• Exchanges hello packets to get neighbor information

• Proactive protocol

• Table based protocol

• Reduces the effect of flooding

1.9 Mac Layer Protocols





• It does not consider the network control, it only consider the user traffic.

• Its performance is totally relying on intermediate nodes.

• It is designed for ideal situation where all nodes are doing their work fair but it

is impractical.

1.10 Composition of Thesis

This thesis is organized as follows

• In Chapter 2, different broadcast techniques and their comparisons are

presented. Multimedia communication and malicious node detection is also

explained.

• In Chapter 3, problem statement is given.

• In Chapter 4, performance evaluation of broadcast techniques and OLSR

preference list is discussed.

• In Chapter 5, network control is added to enhance the mathematical model of

relevance based approach.

• Impact of malicious node is given in Chapter 6.

• Performance evaluation of video streaming in VANETs and secure

multimedia broadcast frame for VANETs is proposed in Chapter 7.

• Validation of secure broadcast frame work is presented in Chapter 8.

• Conclusion is given in Chapter 9.

Chapter #2 Related Work


CHAPTER #2

RELATED WORK





• Collision may cause damage: Because of the deficiency of backoff

mechanism, the lack of RTS/CTS dialogue, and the absence of collision

detection may cause collisions and damages.

2) Probabilistic scheme [53] reduces the collision, contention and redundant

messages in dense network as it broadcast the messages with fixed probability. But in

sparse network all the vehicles can’t receive the same packets with small probability.

If probability is high, its works same like flooding. So its performance is greater in

dense network as compared to sparse network.

3) Counter based technique [55] is a probabilistic approach that is used to analyze

the redundant messages. It use counter to record the redundant message. Whenever

the redundant message is received, the counter is incremented by one. The counter is

compared with certain threshold value if it is less than it, the packet is forwarded

otherwise the packet is discarded.

4) Distance based scheme first calculates the distance between itself and its

neighbor vehicles. Then it compares the distance with threshold. If the distance is

greater than threshold it forwards the packet otherwise it ignores the message [53].

5) Location based scheme first calculates the coverage area with help of sender

location. The vehicle will ignore the packet if area is smaller than a threshold value,

otherwise the packet will be broadcast [56].

6) A well known and widely used technique for broadcast is by using tree but it is

inappropriate for ad hoc networks, because of dynamic nature of network. An

efficient and reliable tree based broadcasting technique is presented in [57], which is

stable even in case of dynamic network. The main theme is to maintain a spanning

tree in the network, and then do the broadcast with the help of it.



Figure 2.1: Broadcast Approaches in Adhoc Networks [58].



7) Joon et al [59] proposed Implicit Neighbor Knowledge Routing in adhoc

networks. Neighbor Knowledge methods are used to maintain a table that contains the

information of its neighbor vehicle. A Vehicle uses this information to broadcast the

messages. All vehicles share hello packets with their neighbors to get current

information. They store this information in their table for future use. Neighbor

Knowledge methods totally rely on the exchange of hello packet. Contention and

collision can happen if the interval is short and large interval degrades the

performance of network due to mobility.

8) Gokhan et al [60] proposed Urban MultiHop Broadcast Protocol (UMB). It is

proposed to resolves the reliability, broadcast storm and hidden node problems,

without sharing information among the vehicles.

Most important goals of UMB protocol are

• Collision caused by hidden node is avoided with the help of RTS/CTS in

UMB Protocol

• In order to utilize the channel efficiently, UMB select the furthest vehicle in

the communication range without having the neighbor vehicle information.

• ACK packet is used in UMB to make broadcast reliable.

• Repeater is installed at different places to broadcast the messages in all

directions.

Directional broadcast and intersection broadcast are the two main steps of UMB[60].

Source vehicle selects the furthest vehicle for communication in direction broadcast

where as in intersection broadcast installed repeaters at road segments forward the

packets to destinations.



9) Hao proposed “A Mobility-Centric Data Dissemination Algorithm for Vehicular

Networks” (MDDV) [11]. It is designed to work competently in network where

mobility is high and topology is dynamic. Local information is stored by vehicles and

they used this information to perform the broadcast. It merges the idea of

opportunistic forwarding, trajectory based forwarding and geographical forwarding.

Trajectory based forwarding is a scheme to disseminate the information in dense

vehicular ad hoc network along predefined curve. [61]

Geographical forwarding is used for routing decisions. To forward packet to the

destination, a vehicle broadcast the packet to a vehicle that is near to the

destination[62].

An opportunistic forwarding [63] has three functions (store, copy and

forward).Whenever a vehicle receives a message; it stores the information and sends a

copy of this message to destination node.

MDDV try to enhances the delivery efficiency and solve the broadcast storm

problem. But it still have some short coming that it does not differentiate between

message types and forwards surplus messages without knowing its relevance.

Redundant information is increased as multiple nodes in the network that broadcast

the same information to their neighbors in order to increase the reliability.

10) Timo designed relevance based approach [48] for vehicular adhoc network as

the speed of vehicles is very high and they have limited time to exchange message so

they forward only relevant and important messages and discard the low priority

messages. Relevance based approach methodology is defined as, first compute the

relevance value of message with the help of three resources (vehicle context, message

context information context).Then allocate the medium to the messages according to

their importance. In this way low priority traffic can’t get the medium more than high





Sequence numbers of packets are useful in order to analyze the network congestion

[66]. With the help of sequence number vehicles dynamically adjust the contention

window and improve the performance.

13) Luca proposed Directional Broadcast Forwarding of Alarm Messages in

VANETs [67]. Medium Access Control and high mobility in VANETs affects the

throughput of routing techniques. Core idea of this scheme is to support the safety

applications in VANETs by solving the design issues of routing techniques. Routing

for emergency applications in C2C networks using Trajectories (REACT) which have

both characteristics of position and trajectory based routing.

REACT is composed of two algorithms

• Forwarding Decision Algorithm (FDA)

• Topology Discovery Algorithm

14) Jason proposed motion vector (MoVe) algorithm, which exchange hello

messages between the neighbors to find the closest destination and do opportunistic

broadcast with the help of velocity information [68]. They compare and analyze five

opportunistic techniques with the help of simulation and measure their throughput and

end to end delay in VANETs environment. The main idea of MoVe is the sharing of

mobility information, which can improve the performance of network.

15) Yu proposed Location based Broadcasting for dense mobile ad hoc networks

[69]. Broadcast techniques are designed to disseminate the information to all nodes in

adhoc networks. Mobility plays great impact on broadcast techniques. Proposed

scheme depends on distribution of mobile nodes rather than topology. They defined

certain constraints on mobility, so that all nodes get the information.



16) Stefan proposed “MISTRAL” algorithms for Flooding in mobile adhoc

networks [70]. Compensation packets are disseminated by all nodes and use forward

error correction. Proposed scheme doesn’t depend on neighbor information so it

works fine in network where mobility is high. They evaluate the performance of

algorithms through simulation and comparison with probabilistic approach. Mistral

achieves more node coverage as compared to probabilistic scheme. If data packet is

retransmitted then compensation packets will not be sent.

17) Lok determines the impact of end to end delay, buffer size and number of

vehicle on broadcast communication in VANETs city environment [71]. Mobility in

dense and sparse network affects the performance of reliable message delivery in

VANETs scenario. The core contribution of Lok is to analyze the traffic features like

density and congestion in a city environment of VANETs.

18) Goya explains Requirements for Packet Forwarding in (VANETs) [72].

Where, few vehicles are unwilling to forward the information to their neighbor which

will cause accidents and degrades the performance of network. Thus, there is a need

of cooperation between the vehicles. Since due to mobility and traffic pattern,

techniques design for MANETs will not work fine in VANETs domain. Goya

proposed a technique to overcome this problem in VANETs scenario.

19) Tonguz proposed the Distributed Vehicular Broadcast (DV-CAST) protocol

[73]. It disseminates using multihop technique for broadcast protocol in dense and

sparse network for VANETs. In order to broadcast the information, DV-CAST

depends on topology information and solves the broadcast storm problem. They also

analyze the reliability and throughput of DV-CAST in different traffic conditions.

DV-CAST has the following features given below.



• It is designed to work under different traffic situation

• It uses hello packets and rely on local information

20) Busson proposed a generic framework to analyze the performance of

broadcast techniques in VANETs [74]. Proposed scheme is based on Palm Calculus

and point processes to locate the position of vehicle. They focus on famous algorithms

and measure their performance. This technique is not for specific radio situation. It

facilitates us to analyze the impact of frame error rate of broadcast techniques in

VANETs.

21) Slavik proposed stochastic broadcast to solve the data dissemination issue in

VANETs [75]. Several broadcast techniques proposed for MANETs don’t provide the

privacy where as it is essential in VANETs. Stochastic broadcast is easy to implement

as it depends on only local information and all vehicles within VANETs measure their

probability with which they will broadcast the information to their neighbors. It is

very difficult to choose the value of probability to broadcast information. In sparse

network, the nodes are far away from each other and isolated. There is less shared

coverage in sparse networks as compared to dense network. So nodes in sparse

network can’t get the packet if probability is low. If probability is high it produces

collision, contention and redundant messages in dense networks and works similar as

flooding.

22) Labiod proposed trajectory based routing protocol to enhance the data delivery

in VANETs [76]. It is a broadcast protocol and requires no neighbor information as

required in knowledge neighbor methods. Whenever a vehicle receives information, it

uses vehicle position, trajectory and transmitter location in order to forward or

discard. This information is already attached within the packet. With the help of

simulation, results of proposed scheme are compared with the existing techniques.



Following are the achievement of proposed scheme

• Control overhead is reduced

• Length of route is shortened

• Reliable delivery

• Require no neighbor information

• End to end delay is reduced

23) Li designed opportunistic broadcast protocol (OppCast) which reduces the

transmission and make the communication faster and enhances the packet reception

ratio [77]. This scheme is composed of two steps. In first step, it tries to make the

broadcast information faster and in the second step it enhances the packet reception

ratio. Following are the achievements of proposed scheme

• This technique is applied at each hop in order to minimize the propagation

delay

• It solves the hidden node problem.

• High reliability

• Faster message propagation

• Packet collision is reduced

24) Biswas proposed proxy signature based technique [78] for secure message

dissemination in a VANETs scenario. In order to achieve security in VANETs,

proposed technique alters the proxy signature approach. Following are the

achievement of proposed scheme

• Message integrity,

• Authentication of information

• It is appropriate to IEEE 802.11p

• Resilience against Forgery



25) Laouiti designed reliable opportunistic broadcast protocol [79] for VANETs.

Following are the achievements of proposed scheme

• It reduces the effect of shadow on broadcast information

• High data delivery

• Low average delay.

2.2 Comparisons of Different Protocols

Comparison of different broadcast protocols is shown in the below Table 2.1. We

analyzed the protocol in terms of various parameters for e.g. contention, collision,

congestion, performance, reliability. None of existing schemes is ideal for all

scenarios. Simple flooding works better in sparse network and probabilistic works

better in dense network.



Table 2.1: Comparison of Broadcast Protocols for VANETS [80]

PROTOCOLSPROTOCOLSPROTOCOLSPROTOCOLS RELIABILITYRELIABILITYRELIABILITYRELIABILITY PERFORMANCEPERFORMANCEPERFORMANCEPERFORMANCE CONGESTIONCONGESTIONCONGESTIONCONGESTION REBROADCASTREBROADCASTREBROADCASTREBROADCAST COLLISCOLLISCOLLISCOLLISIONIONIONION CONTENTIONCONTENTIONCONTENTIONCONTENTION

Simple Flooding Very high moderate Very high redundant severe Very high

Probabilistic Scheme

Moderate moderate Low Controlled moderate low

Counter-Based Scheme

Moderate moderate Low Controlled moderate low

Distance Based Approach

Moderate moderate Low Controlled low moderate

Location Based Approach

High high Low Efficient low moderate

Neighbor Knowledge Methods

moderate moderate moderate controlled Period dependent (moderate)

Period dependent (moderate)

Tree Based Broadcast

high high Very low Efficient low Very low

UMB high high moderate controlled low moderate

MDDV high high Low controlled low low

Relevance-based approach

moderate High Low Efficient low low

MHVB high high Very low Efficient high low

Adaptive broadcast protocol

high high moderate Inefficient high high





of













The main contribution is to choose correct hardware and software effect the performance

of multimedia communication in VANETs.

2.5 Detection of Malicious Data and Malicious Node

Maxim presents the need and importance of security in VANETs in order to fulfill the

security requirements [96]. They proposed security architecture which will provide

security and privacy.

VANETs depend upon the vehicle to vehicle communication, which allows the

malicious node to send malicious data in the network. Golle proposed a technique to

detect and correct the malicious data [97] in VANETs. The technique is based upon the

sensor data, collected by vehicles in the VANETs and neighbors information. Redundant

information from neighbors and position of vehicle helps out to detect the malicious data.

Xiao proposed a scheme to localize and detect Sybil vehicles in VANETs on the basis

of the signal strength [98]. With the help of signal strength a vehicle can verify the

position of other vehicles and eliminate the malicious nodes in VANETs. Xiao first

proposes position verification techniques with help of signal strength but it still has some

shortcomings i.e. spoof attack can be possible and data is inconsistent. In order to

overcome this weakness, they propose another solution to prevent the malicious node in

VANETs. Two static algorithms are proposed with help of traffic patterns and base

station. These algorithms are designed to verify the position of the vehicle and reduce the

effect of malicious node on communication in VANETs. Following benefits are achieved

by using this algorithm

• Error rate is reduced



• Malicious nodes is easily detected

• It is not hardware dependent

In order to improve performance, selfish or malicious nodes must be captured and

removed from VANETs. But it is very difficult to detect these nodes due to lack of

infrastructure and dynamic nature of VANETs as compared to any other adhoc networks.

Raya also proposed a framework feasible to the features of vehicular environment [99]. It

detects and prevents the effect of malicious node in VANETs scenario.

2.6 TestBed

Performance evaluation of protocols in real world is a challenging task for the

researcher in the field of VANETs. There is some stuff available in evaluating the quality

of 802.11 and 802.11e in VANETs scenarios with the help of simulators and limited

work exists in analysis the multihop protocol in real time scenarios.

Jose evaluates the performance of OLSR protocol in urban and highway scenario by

making VANET testbed with the help of 802.11b protocol [100]. They measure packet

delay, packet loss, and throughput and proof that OLSR protocol is theoretically working

fine but practically it is not suitable for VANETs scenarios. Routing tables of OLSR is

not updated quickly due to high mobility in VANETs.

Carolina proposes DemonstRator for Intelligent Vehicular Environments (DRIVE),

which provides the evaluation of VANET services in real world with the help of testbed

[101]. DRIVE is consisting of hardware and software components. Software provides the

easy development of VANET services and hardware consist of following components.



• Sensors

• Antenna

• CarPC

• Wi-Fi or UMTS

DRIVE provides the multiple feature that existing testbed don’t have like Vehicle to

vehicle, vehicle to road and vehicle to infrastructure communication.

Moez experimentally proves the feasibility of multimedia application [93] in VANETs

scenario by using IEEE 802.11[8]. Due to high cost only few real time experiments exist

as compared to simulation analysis. The main contribution is that speed, distance and

environment (city, urban, highway) will affect the quality and performance of multimedia

data in VANETs.

Several protocols are being developed for vehicle to road side and Vehicle to Vehicle

communication. Ali et al [102] analyzes the existing WI-FI protocol for vehicle to vehicle

with the help of real time experiments. Their study focuses on the feasibility of IEEE

802.11 protocol and measures the data that is shared during the scenario. Experiment

results prove that WIFI is suitable for vehicular communication and he suggests different

applications that are suitable for VANETs.

Peter et al. analyze several factors that affects the performance of VANETs and also

proposes new test environment for VANETs [103]. This real time design is very helpful

for researcher in the field of VANETs to measure the performance of network. Karim et

al. propose that distance and velocity plays an important role in the establishment of

connection [104]. They perform real time experiments with the help of ten cars moving in

the freeway and observe the effect of velocity on the establishment of connection.

Chapter #3 Problem Statement


CHAPTER #3

PROBLEM STATEMENT









• Vehicles don’t overtake each other

• Messages produced at same time with same area don’t cause collisions

• Vehicles can’t sense the availability of transmission channel

• Transmission is not influenced by obstacles on the road

• Hidden terminal problem is not considered.

So there is a need to enhance the existing simulator to overcome the above mention

problems and test the performance of broadcast approaches in the VANETs scenario

using real testbed.

The problem is to enhance the mathematical model of relevance based approach and

to design a new data dissemination scheme that is secure and it considers not only the

user traffic but also the network control.

Chapter #4 Performance Evaluation of Broadcast Approaches


CHAPTER #4

PERFORMANCE EVALUATION OF

BROADCAST APPROACHES



4.1 Introduction

Broadcast is mainly used in VANETs for communication. Broadcast techniques are

proposed to reduce collision, contention, redundant messages and hidden node problems

etc. and improve the message reliability. But there is no comprehensive analysis and

performance evaluation of broadcast exists. In this chapter we simulate the existing

broadcast techniques with help of NS-2 simulator in VANETs scenario and determine

their pro and cons in sparse and dense network. After that we shall modify the OLSR

protocol and a simulation result shows that network load is reduced.

4.2 Proposed Study

In this study we evaluate the performance of simple flooding and relevance based

approach in VANETs scenario. The mobility model we use is Manhattan Mobility Model

[35] and Generic Mobility Simulation Framework generates the traffic [36]. We perform

simulation with help of Network Simulator (NS-2) [37]. Different parameters are used for

VANETS simulation [106] and are shown in Table 4.1 for both scenarios.

First we evaluate the simple flooding in VANETs scenario and measure its

performance. We also analyze the redundant message produced by it. Then we simulate

the relevance based approach and measure its performance in terms of priority.



Table 4.1: Simulation Parameters

4.3 Performance Evaluation of simple flooding

In this study we have fifty vehicles, moving with a speed of speed 20 to 30 m/s and

simulation time is 50 seconds. Figure 4.1 shows the number of packets received by all

vehicles during the simulation.

Simple Flooding has the problem of collision, contention and redundant messages.

Figure 4.2 shows the redundant messages produced during simulation. The number of

redundant messages increases with time because every node has sent the packet to its

neighbor no matter if its neighbor already has that packet.

Simple flooding does not discriminate between safety and route messages and give all

messages same importance. So the problem is to improve the simple flooding so that it

can consider the importance of messages and less redundant messages are produced.

It is clear from figure 4.1 and 4.2 that a lot of redundant message are produced if we use

simple flooding in VANETs. In the beginning the number of redundant messages greater

than number of actual message received. But with time the redundant messages increase

more gradually than the number of actual message received. .It produces 10 to 15 times

more surplus information as compared to relevant information.

Parameters Values

Channel Wireless

Vehicles 50

MAC protocol 802.11

Radio Propagation Model Two-Ray Ground

Time 50 s

Routing Protocol DSDV



Figure 4.1: Simple flooding with 50 vehicles Figure 4.2: (a) Simple Flooding Redundant packets

Fig 4.2: (b)Comparsison on Relevant and redundant Messages

4.4 Performance Evaluation of Relevance Based approach

Figure 4.3 shows the performance of Relevance Based approach. Four different types

of messages i.e. Safety messages, Route messages, weather messages, common messages

are exchanged between fifty vehicles having speed of 72Km/hr to 108Km/hr.



Existing Broadcast Techniques has no mechanism of message differentiation and

assign the equal priority to all messages. But relevance based approach is the technique

that assigns higher priority to safety messages, discard the surplus messages and share

only relevant messages within VANET.

Figure 4.3 Relevance Based Approach with 50 vehicles



4.5 Efficient Mechanism to Exchange Relevant Messages in VANETS

Vehicular Adhoc Networks are subclass of mobile adhoc network. Broadcast is a

commonly used technique for communication. OLSR is a table driven proactive protocol

that exchanges hello packet to get information of network at each vehicle. We modify the

hello packet and add a new parameter called preference list, which contains interest of the

vehicle and data which current vehicle has. In this way network load is reduced and due

to mobility we have very short time to exchange data. So we only forward data according

to neighbor preference.

4.6 Proposed Solution:

We modify the hello packet of OLSR protocol. Now the hello packet also contains

the preference list of user. This list indicates that what type of information user has and

what type of information he wants from others. If he needs information about parking, he

should not get message about fuel station, accident and weather. We shall first discuss the

different scenarios and then by using simulation prove that proposed approach gives

better results than existing one.

Scenario 1

In scenario 1 we have four vehicles V1, V2, V3, and V4 as shown in figure 4.4. These

vehicles form a temporary vehicular adhoc network for information sharing Using hello

messages they come to know the following information. First preference of their

neighbors which they will store in preference table for future communication. Secondly

is the data which other vehicle has in their cache.



Figure 4.4: Basic Scenario Figure 4.5: New Vehicle joins VANETs

Figure 4.6: V3 detected an accident

Scenario 2

In Scenario2 a new vehicles V5 joins the VANETs as shown in figure 4.5. V1 and V2

share hello message with V5 to get the preference of it.



Scenario 3

Suddenly V3 detected an accident as shown in figure 4.6. V2 and V4 is neighbor of it.

So he has to forward data to its neighbor, but he sends information to V2 only and does

not send any information about accident to V4. Because in preference table V2 mentions

that he needs accident information and V4 says that he does not need any accident

information. Similarly V2 send accident information only to V5 and no data to V1.

Figure 4.7: V1 detected Traffic Jam Figure 4.8: V1 detected accident and Traffic Jam

Scenario 4

Suddenly V1 detected traffic Jam as shown in figure 4.7. V4 and V5 is neighbor of it.

So he has to forward data to its neighbor, but he sends information to V4 only and does

not send any information about accident to V5. Because in preference table V4 mentions

that he needs Traffic Jam information and V5 says that he does not need any traffic jam

information. Similarly V4 sends traffic information to V3 and V3 does not send it to V2.



Scenario 5

Suddenly V1 detected an accident and traffic Jam as shown in figure 4.8. So it checks

its preference table for broadcast. He forwarded accident information to V2 and traffic

information to V4. Similarly V2 sent accident information to V5, V3 and V4 sends traffic

information to V3 and V3 does not forward it to any neighbor because he has no entry for

traffic jam.

4.7 Simulations and Results

In order to validate our proposed scheme, we implement the above scenarios with

increase the number of vehicles to get better and real environment. We used NS-2, a

network simulator, to simulate the existing behavior of OLSR under different scenarios.

Mobility is generated using Rice Mobility generator and mobility trace file are available

at [105] with 1188 number of roads and 383 number of intersections. But the problem is

that we have limited number of vehicles exist in the mobility trace file.

The simulation is performed by using Network Simulator (NS-2) and parameter used for

scenarios are shown in Table 4.2

Table 4.2: Simulation Parameters

Parameters Values

Channel Wireless

Antenna Type Omni directional

MAC protocol 802.11

Radio Propagation

Model

Two-Ray Ground

Routing Protocol OLSR



We consider an area of 3000m x3000m with vehicles moving at a speed of 40Km/hr

to 70 Km/hr. User specify their preference and we measure the performance of different

types of messages are exchanged by vehicles.

Figure 4.9: Throughput of accident Information

Figure 4.10: Throughput of Traffic Jam Information



Figure 4.11: Throughput of Fuel Information

Figure 4.9 shows the number of relevant accident messages that vehicles received for

which they have subscribed for. Vehicles number 0, 2, 4, 6, 8…48 needs accident

information. In figure 4.10, different vehicles ranges from 0, 3, 6, 9, 12….48 have shown

their interest in traffic jam information and we measure their performance.

Figure 4.12: Relevant Parking Information Sharing



Figure 4.13: Total Throughput of Information Sharing

In figure 4.11, vehicle 0, 5, 10, 15…49 needs fuel station information. These vehicles

have no interest in accident and traffic jam information so they measure their

performance according to their interest. In figure 4.12, vehicle 0, 10, 20, 49 need parking

information. We measure their throughput according to their interest. In figure 4.13, we

measure the performance of all the vehicles according to their interest.

Figure 4.14: Throughput of Surplus Accident Information



Figure 4.15: Throughput of Surplus Traffic Jam Information

Figure 4.16: Throughput of Surplus Fuel Information



Figure 4.17: Throughput of Surplus Parking Information

Figure 4.14 shows the number of surplus accident messages that vehicles received for

which they have not subscribed for. In figure 4.15, different vehicles ranged from 0, 2,

4…48 received traffic jam information. These vehicles have no interest in traffic Jam

information.

Figure 4.18 Throughput of Total Surplus Information



In figure 4.16 shows the vehicle that was interested in accident and traffic jam

information but they get surplus fuel station information. Figure 4.17 shows the surplus

parking information. Vehicles need fuel information but they are getting parking

information. In figure 4.18, we measure the total surplus information. With the help of

preference list 80% of surplus information is removed.

4.8 Conclusion

In this chapter we analyze the existing broadcast techniques their pros and cons in

sparse and dense network. After that we measure the performance of broadcast schemes

with help of NS-2 simulator in VANETs scenario. Simulation shows that simple flooding

produces a lot of redundant messages. It works fine in sparse network but in dense

network its performance is not fair and it also has no priority mechanism. Relevance

approach has less redundant message and it gives priority to safety messages than other

messages. But it still has some drawbacks. Like it does not consider network control and

proposes for ideal scenario where no malicious node exists. Relevance approach can be

enhanced so that it can consider the network control and simulate it in real scenario by

considering the impact of malicious node.

OLSR is a table driven proactive protocol that exchanges hello packet to get

information of network at each vehicle. By modifying the OLSR protocol and inserting a

preference list in hello packet so that the number of surplus and redundant messages can

be reduced.

Chapter #5 Enhanced Relevance Based Approach for Network Control


CHAPTER #5

ENHANCED RELEVANCE BASED APPROACH

FOR NETWORK CONTROL















Ne two rk C o ntro l in R e le v an c e B as e d app roac h

0

200000

400000

600000

800000

1000000

1200000

10 20 30 40 50

Time [s ]

Glo

ba

l B

en

ifit

G lobal B enifit E nhanc ed G lobal B enifit

Figure 5.3: Comparisons of GB and EGB

Figure 5.4: Network Control

Ne two rk C o ntro l in R e le v an c e B as e d app roac h

0

100

200

300

400

500

600

700

800

10 20 30 40 50

Time [s ]

No

of

pa

ck

ets

re

cie

ve

d

Network Traffic Us er Traffic



Chapter #7 Performance Evaluation of Video Streaming in VANETs


CHAPTER #6

IMPACT OF MALICIOUS NODE ON BROADCAST

SCHEMES







Figure 6.1: Global Benefit with 100 vehicles in ideal scenario



Figure 6.2: Global Benefit in real scenario (intelligent malicious node)

Figure 6.3: Global Benefit in real scenario

6.3 Information Sharing in Vehicular Adhoc Network

Relevance based approach is the only scheme that forward relevant message for

sharing and discard the surplus messages. But it has certain flaws. The relevance based







0

200000

400000

600000

800000

1000000

1200000

10 20 30 40 50

Time [s]

Message Benefit Enhanced Message Benefit

Glo

ba

l B

en

efi

t

Figure 6.4: Improvement due to mathematical

Figure 6.5: improve due to virtual queue

6.6 Improvement due to Virtual Queue

Figure 6.5 shows the performance of simple 802.11e and virtual queue with 802.11e

with the help of safety and route messages. In this study 150 vehicles are exchanging

information with each other. In simple 802.11e, there is no mechanism of priority

0

50000

100000

150000

200000

250000

300000

350000

400000

450000

10 20 30 40 50

Time [s]

802.11e Virtual Queue

Glo

ba

l B

en

efi

t



assignment. This problem is resolved by virtual queue. So its global benefit is greater

than simple 802.11 e because it does not allow lower priority traffic to get more medium

than higher priority traffic.

6.7 Improvement due to Virtual Queue and Mathematical Model

First we check the improvement due to mathematical model and virtual queue

separately but now we consider the impact of both on the global benefit of network.

Figure 6.6 above shows that global benefit of existing and enhance relevance based

approach due to virtual queue and mathematical model. Enhanced relevance based

approach has higher global benefit because it resolves the problem of priority mechanism

and ignorance of network control traffic.

Figure 6.6: Improvement due to virtual queue and mathematical model

6.8 Comparison

This study shows the comparison of simple virtual queue with the overall impact of

virtual queue and mathematical model. Similarly we compare simple mathematical model

0

200000

400000

600000

800000

1000000

1200000

10 20 30 40 50

Time [s]

Message Benefit Enhanced Message Benefit

Glo

ba

l B

en

efi

t



with overall impact of virtual queue and mathematical model.

Fig 6.7 shows the global benefit due to Message Benefit (MB), enhance message benefit

(EMB) and virtual queue with EMB. It is clear from figure that global benefit by using

virtual queue with EMB is greater than simple EMB because within a queue there is no

priority mechanism available.

Figure 6.7: Comparison of mathematical model with both (VQ and EMB)

Fig 6.8 shows the global benefit due to 802.11e, Virtual Queue and EMB with virtual

queue. It is clear from figure that global benefit by using EMB with virtual queue is

greater than 802.11e and simple queue because in simple queue we don’t have to

discriminate between user traffic and network traffic.

0

200000

400000

600000

800000

1000000

1200000

10 20 30 40 50

Time [s]

Message BenefitEnhanced Message Benefit(EMB)Virual Queue + EMB

Glo

ba

l B

en

efi

t



Figure 6.8: Comparison of virtual queue with both (virtual queue and mathematical

model)

6.9 Impact of Malicious node

In this study we consider the impact of malicious node on EMB, Virtual Queue and

both (EMB with virtual queue).Figure 6.9 shows that 50 vehicles are moving at high

speed and share safety and comfort information with each other. First we simulate the

MB and EMB in ideal scenario that no malicious node exists and all nodes try to improve

the benefit of network rather than their own benefit. After that we simulate the EMB in

real scenario that malicious node exists and damage the performance of the network.

Figure 6.9 shows that global benefit of EMB in real scenario lies between the EMB and

MB in ideal scenario.

Figure 6.10 shows that 150 vehicles, exchanging information with each other. First we

simulate the 802.11e and virtual queue in ideal scenario that no malicious node exists and

all nodes try to improve the benefit of network rather than their own benefit. After that

we simulate Virtual queue in real scenario that malicious node exists and damages the

0

200000

400000

600000

800000

1000000

1200000

10 20 30 40 50

Time [s]

802.11eVirtual Queue(VQ)VQ + EMB

Glo

ba

l B

en

efi

t



performance of the network. Figure 6.10 shows that global benefit of EMB in real

scenario lies below than 802.11e and Virtual Queue in ideal scenario.

Figure 6.9: Impact of malicious node on EMB

Figure 3.10: Impact of malicious node on Virtual Queue (VQ)

0

200000

400000

600000

800000

1000000

1200000

10 20 30 40 50

Time [s]

Message BenefitEnhanced Message Benefit(EMB)Impact of malicious node on EMB

Glo

ba

l B

en

efi

t

0

50000

100000

150000

200000

250000

300000

350000

400000

450000

10 20 30 40 50

Time [s]

802.11eVirtual Queue(VQ)impact of malicious node on VQ

Glo

ba

l B

en

efi

t



Figure 6.11 Impact of malicious node on Enhanced Message Benefit and Virtual Queue

Figure 6.11 shows that 150 vehicles are moving at high speed and share safety and

comfort information with each other. First we simulate the MB and VQ with EMB in

ideal scenario that no malicious node exists and all nodes try to improve the benefit of

network rather than their own benefit. After that we simulate VQ with EMB in real

scenario that malicious node exist and damage the performance of the network. Figure

6.11 shows that global benefit EMB with VQ in real scenario lies between the EMB with

VQ and MB in ideal scenario.

6.10 Conclusions

0

200000

400000

600000

800000

1000000

1200000

10 20 30 40 50

Time [s]

Message BenefitVQ + EMBImpact of malicious node on VQ + EMB

Glo

ba

l B

en

efi

t



CHAPTER #7

PERFORMANCE EVALUATION OF VIDEO STREAMING

IN VEHICULAR ADHOC NETWORK



second







Figure 7.9: PSNR (SD in real scenario) Figure 7.10: Delay (SD in real scenario)

Figure 7.11: SR (SD in real scenario) Figure 7.12: RR (SD in real scenario)

0

10

20

30

40

50

0 100 200 300 400

Frame Number

PS

NR

(d

b)

0

0.1

0.2

0.3

0.4

0.5

0 100 200 300 400

Frame Number

De

lay

0

20000

40000

60000

80000

0 2 4 6 8 10121416 1820 22

Time

Se

nd

ing

Ra

te

0

10000

20000

30000

40000

50000

60000

0 2 4 6 8 10121416 1820 22

Time

Re

ce

ivin

g R

ate



Figure 7.13: PSNR (OD in real scenario) Figure 7.14: Delay (OD in real scenario)

Figure 7.15: SR (OD in real scenario) Figure 7.16: RR (OD in real scenario)

0

0.05

0.1

0.15

0.2

0.25

0.3

0 100 200 300 400

Frame Number

De

lay

0

10000

20000

30000

40000

50000

60000

0 2 4 6 8

Time

Re

ce

ivin

g R

ate

0

20000

40000

60000

80000

0 2 4 6 8 10121416 1820 22

Time

Se

nd

ing

Ra

te

0

10

20

30

40

50

0 50 100 150

Frame Number

PS

NR

(d

b)





Step 3) On the basis of reply, SMBF decides to forward or discard the message.

Step 4) Redundant Messages are discarded.

Step 5) New Information is sent for Message Benefit.

Step 6) Relevance value is sent to SMBF.

Step 7) Request to MNV for malicious node verification.

Step 8) Receives Reply from MNV and on basis on reply SMBF decides to forward or

discard the message.

Step 9) If the node is malicious, data is discarded.

Step 10) Request is sent to MDV to verify the malicious data.

Step 11) Receives Reply from MDV and on basis on reply SMBF decides to forward or

discard the message.

Step 12) If the data is malicious, it is discarded.

Step 13) If the node and data are not malicious then it is forwarded to Vehicles B.

Figure 7.17: Secure Multimedia Broadcast Framework (SMBF)



Redundant Information: Every node maintains a table of Message ID of currently

received messages. We assume that the Message ID is unique and on basis of it we detect

the redundant messages.

Message Benefit: We calculate the priority of each message. Safety Message gets higher

priority than any other messages.

Malicious Node Verification: We detect the malicious node on basis of signal strength.

Malicious Data Verification: We detect the malicious data on basis of existing messages

from neighbor and also on the basis of position of node.

7.5 Implementation and Results

In this study we evaluate the performance of multimedia streaming in VANETs

scenario. The mobility model we use is Manhattan Mobility Model and EvalVid

generates the multimedia traffic. We perform the simulation with help of NS-2 on

Cygwin and parameter used in simulation is mentioned in the table 7.1.

Table 7.1: Simulation Settings

7.5.1 Study I

We simulate the multimedia traffic in two different scenarios. First we measure the delay,

PSNR and throughput in scenario where there is no mechanism, which exists for

detection of malicious data and malicious node as shown in figures [7.18] [7.19] [7.20].

Parameters Values

Channel Wireless

Vehicles 3

MAC protocol 802.11

Radio Propagation

Model

Two-Ray Ground

Time 50 s

Data type multimedia



0

0.2

0.4

0.6

0.8

1

1.2

0 50 100 150 200 250 300Frame Number

De

lay

In this study we have three Vehicles (V1, V2 and V3) are moving at very high speed.V2

and V3 want to share a multimedia traffic with V1 and V2 is a malicious node that sends

malicious data to V1 and affects the performance of network.V1 has no frame work to

determine the validity of data and it considers both V2 and V3 are fair nodes. The delay

in this case is higher and throughput is lowered because of the effect of malicious data.

Figure 7.18: PSNR Figure 7.19: Delay

Figure 7.20: Throughput

0

5

10

15

20

25

30

35

40

45

50

0 50 100 150 200 250 300Frame Number

PS

NR

48000

49000

50000

51000

52000

53000

54000

55000

56000

57000

58000

0 1 2 3 4 5 6 7 8 9 10 11 12Time

Th

rou

gh

pu

t



0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

0 1 2 3 4 5 6 7 8 9 10 11 12Time

Th

rou

gh

pu

t

7.5.2 Study II

Now we consider the same scenario as the above one. But in this case V1 has the

SMBF to determine the redundant messages, malicious node and malicious data. We

measure the delay, PSNR and throughput by applying the SMBF as shown in figures

[7.21] [7.22] [7.23]. Performance of the network is not affected in this case because

MDV detects the malicious data on basis of existing messages from neighbor and also on

the basis of position of node. So in this case delay is lower and throughput is higher

because the malicious data does not affect the network.

Figure 7.21: PSNR of SMBF Figure 7.22: SMBF Delay

Figure 7.23: SMBF Throughput

0

5

10

15

20

25

30

35

40

45

50

0 50 100 150 200 250 300Frame Number

PS

NR

0

0.05

0.1

0.15

0.2

0.25

0.3

0 50 100 150 200 250 300Frame Number

De

lay



Figure 7.24: Delay Comparison

Figure 7.25: Throughput Comparison

7.6 Comparisons

At last we measure the comparison of study I and study II to determine how much

delay increases and throughput decreases, when there is no framework for the detection

of malicious data and malicious node. Figure 7.24 and figure 7.25 shows that delay is

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

0 50 100 150 200 250 300

Frame Number

De

lay

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

0 1 2 3 4 5 6 7 8 9 10 11 12Time

Th

rou

gh

pu

t



much lower when SMBF is applied and throughputs also increase much more by using

SMBF. Results show that the throughput of multimedia traffic improved 20% to 40%

while using SMBF

7.7 Conclusion

Chapter #8 Validation of Secure Broadcast Framework using VANETs


CHAPTER #8

VALIDATION OF SECURE BROADCAST

FRAMEWORK USING VANETS



8.1 Introduction

We proposed a framework for secure broadcast communication in VANETs and measure

its performance with of NS2 and real testbed scenario.

8.2. Proposed Study

Our proposed SBF framework is composed of four modules (Redundant Information,

Message Benefit, Malicious Node Verification (MNV) and Malicious Data Verification

(MDV)) as in figure 8.1. SBF is consist of following steps which are given below.

Figure 8.1: Secure Broadcast Framework



8.3 Testbed Implementation and Results

In this study we validate the SBF in VANETs scenario using testbed. We measure the

global benefit of SBF in three different scenarios and compare its performance with

normal broadcast mechanism. Using java socket we make two servers that share

information and measure the global benefit.

8.4 Study I

In this study we consider two vehicles that are stationary in the parking of King Saud

University. Vehicles are sharing messages using normal broadcast mechanism (NB) and

secure broadcast framework. As shown in figure 8.2, global benefit of SBF is more than

NB. Redundant and malicious data reduce the global benefit of NB where as in SBF, it is

detected and is not broadcasted as in the case of NB.

Figure 8.2: Global Benefit of SBF and NB

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 50 100 150 200

time

global benifit

SBF NB



8.5 Study II

In this study we consider two vehicles in the parking of King Saud University.

Vehicle A is stationary and vehicle B is moving towards the stationary vehicle. Vehicles

are sharing messages using NB mechanism and SBF. But in this case vehicles have

limited time to share messages as vehicle B is in the range of vehicle A for 27 seconds.

Global Benefit of SBF is slightly more than NB because there is no redundant and

malicious data, that is forwarded in case of SBF as shown in figure 8.3.

Figure 8.3: Global Benefit of SBF and NB

8.6 Study III

In this study we consider two vehicles that are moving in the parking of King Saud

University and sharing data using NB mechanism and SBF. Due to mobility, global

benefit of SBF and NB is less than the global benefit of study I and study II. Global

benefit of NB is less than SBF because it forwards the redundant and malicious data that

is discarded in case of SBF as in figure 8.4.

0

100

200

300

400

500

600

700

800

0 10 20 30

time

global benifit

SBF NB



Figure 8.4 Global Benefit of SBF and NB

8.7 Study IV

In this study we just see the comparison of SMBF using NS2 simulator and Testbed.

Testbed scenario is same as the above one and simulation results show that in theoretical

global benefit is high as shown in figure 8.5 but in practical its performance is somehow

low than actual one.

Figure 8.5: Global Benefit of SBF, NB and TSBF

0

50

100

150

200

250

300

350

400

0 10 20 30

time

global benifit

SBF NB

0

100

200

300

400

500

600

700

800

0 10 20 30

time

global benifit

SBF NB TSBF

Chapter #9 Conclusion and Future Work


CHAPTER #9

CONCLUSION AND FUTURE WORK





References


REFERENCES

[1] Sunsook Jung, Nisar Hundewale, Alex Zelikovsky, “Energy Efficiency of Load

Balancing in MANET Routing Protocols”, IEEE, 2005.

[2] Corson, Macker, “Informational RFC 2501 MANET Performance Issues”, Jan 1999.

[3] http://nets.rwth-aachen.de/~mesut/manet/manet_en.html.

[4] André Schumacher, Sauli Painilainen, Torsten Luh, “Research Study of MANET

Routing Protocols”, 2004.

[5] Aneel Rahim, Mehboob Yasin, Imran Ahmad, Zeeshan Shafi Khan, Muhammad Sher,

“Relevance Based Approach with Virtual Queue Using 802.11e protocol for Vehicular

Adhoc Networks “, IEEE-IC4, 2009.

[6] Saleh Yousefi, Saeed Bastani, Mahmood Fathy, “On the Performance of Safety

Message Dissemination in Vehicular Ad Hoc Networks”, IEEE Fourth European

Conference on Universal Multiservice Networks, European, 2007.

[7] H. Morimoto, M. Koizumi, H. Inoue, K. Nitadori, “AHS road-to-vehicle

communication system”, IEEE Intelligent Transportation Systems Conference, Tokyo,

1999.

[8] O. Andrisano, M. Nakagawa, R. Verdone, “Intelligent transportation systems: the role

of third generation mobile radio networks”, IEEE Communication Magazine, pp. 144-

151, Sept. 2000.

[9] J. Harri, F. Filali, C. Bonnet, Marco Fiore, “VanetMobiSim: Generating Realistic

Mobility Patterns for VANETs”, ACM VANET’06, September 29, 2006, Los Angeles,

California, USA

References


[10] Aneel Rahim, Imran Ahmad, Zeeshan Shafi Khan, Muhammad Sher, Muhammad

Shoaib, Adeel Javed, Rashid Mahmood, “A Comparative Study of Mobile and Vehicular

adhoc networks”, International Journal of Recent Trends in Engineering, Vol 2, No. 4.

2009

[11] Hao Wu , Richard Fujimoto, Randall Guensler and Michael Hunter,” MDDV: A

Mobility-Centric Data Dissemination Algorithm for Vehicular Networks”, ACM VANET

October 1, 2004, Philadelphia, Pennsylvania,USA

[12] Jeremy J. Blum, Azim Eskandarian, and Lance J. Hoffman,” Challenges of

Intervehicle Ad Hoc Networks”, IEEE Transactions On Intelligent Transportation

Systems, Vol. 5, No. 4, December 2004.

[13] homepage.fudan.edu.cn/~yubohome/References/VANET/VANETResource.htm,

30th June, 2010.

[14] NS2, http://www.isi.edu/nsnam/ns/,30th June, 2010.

[15] Cygwin, http://www.cygwin.com/, 30th June, 2009.

[16] J. Klaue, B. Rathke, and A. Wolisz, "EvalVid - A Framework for Video

Transmission and Quality Evaluation", 13th International Conference on Modelling

Techniques and Tools for Computer Performance Evaluation, pp. 255-272, Urbana,

Illinois, USA, September 2003.

[17] Chih-Heng Ke, Ce-Kuen Shieh, Wen-Shyang Hwang, Artur Ziviani, “An Evaluation

Framework for More Realistic Simulations of MPEG Video Transmission”, Journal of

Information Science and Engineering (accepted).

[18] “EvalVid A Video Quality Evaluation Tool-set”, http://www.tkn.tu-

berlin.de/research/evalvid/, 30th June, 2010

References


[19] CORSIM, http://mctrans.ce.ufl.edu/featured/tsis/Version5/corsim.htm, 30th June,

2010.

[20] groovesim, http://portal.acm.org/citation.cfm?id=1080764, 10 May, 2010.

[21] swan++, http://www.aqualab.cs.northwestern.edu/projects/swans++/,10 May, 2010

[22] Christian J. Adler, Information Dissemination in Vehicular Ad Hoc Networks, 18.

April 2006.

[23] Trans, http://trans.epfl.ch/,15 May, 2010

[24] Roadnav, http://roadnav.sourceforge.net/,15 May, 2010

[25] Cartalk http://www.cartalk2000.net, 15 May, 2010

[26] COMCAR, http://www.comcar.de/, 30th June, 2010.

[27] Car2Car, http://www.car-2-car.org, 30th June, 2010.

[28] Security on Road, http://www.sevecom.org/,30th June, 2010.

[29] eSafetyhttp://ec.europa.eu/information_society/activities/esafety/index_en.htm, 30th

June, 2010

[30] EPFL Vehicular Networks Security Project, http://ivc.epfl.ch/, 30th June, 2010.

[31] Network on wheels, http://www.network-on-wheels.de/about.html, 30th June, 2010

[32] Azzedine Boukerche,” Performance Evaluation of Routing Protocols for Ad Hoc

Wireless Networks”, Mobile Networks and Applications 9, 333–342, 2004

[33] C. Perkins, E. Belding-Royer, S. Das “Ad hoc On-Demand Distance Vector

(AODV) Routing,” Request for Comments 3561, Network Working Group,

http://www.ietf.org/rfc/rfc3561.txt, July2003

[34] C. M barushimana and A. Shahrabi,”Comparative Study of Reactive and Proactive

Routing Protocols Performance in Mobile Ad Hoc Networks”, 21st International

References


Conference on Advanced Information Networking and Applications Workshops

(AINAW'07), IEEE, 2007.

[35] T. Clausen and P. Jacquet, “Optimized linkstate routing protocol (OLSR),” Request

for Comments 3626, MANET Working Group, http://www.ietf.org/rfc/rfc3626.txt,

October2003

[36] P. Jacquet, P. Muhlethaler, T.clausen, A.Laouiti, A. Qayyum. Optimized link state

routing protocol for adhoc networks,IEEE,2001

[37] IEEE 802.11 WG, “International Standard for Information Technology — Local and

Metropolitan Area Networks-Specific Requirements — Part 11: Wireless LAN MAC and

PHY specifications,” 1999.

[38] Min Shen , Dongmei Zhao, ”Throughput Analysis of IEEE 802.11 and IEEE

802.11e MAC”,ACM, The Third International Conference on Quality of Service in

Heterogeneous Wired/Wireless Networks, August 7-9 2006, Waterloo, ON, Canada

[39] Marina Thottan, Michele C. Weigle, “Impact of 802.11e EDCA on Mixed TCP-

based Applications”, ACM, WICON’06 The 2nd Annual International Wireless Internet

Conference, August 2-5, 2006, Boston, MA, United States.

[40] G. Anastasi and L. Lenzini, “QoS provided by the IEEE 802.11 wireless LAN to

advanced data applications: a simulation analysis” Wireless Networks 6 (2000) 99–108.

[41] O. Andrisano, M. Nakagawa, R. Verdone, “Intelligent transportation systems: the

role of third generation mobile radio networks”, IEEE Communication Magazine, pp.

144-151, Sept. 2000.

[42] Jamal N. Al-Karaki , J. Morris Chang, ”A Simple Distributed Access Control

Scheme for Supporting QoS in IEEE 802.11 Wireless LANs”, WCNC 2004 / IEEE

References


[43] Pierre Ansel, Qiang Ni, Thierry Turletti “FHCF: A Simple and Efficient Scheduling

Scheme for IEEE 802.11e Wireless LAN”, Mobile Networks and Applications 11, 391–

403, 2006

[44] Jose Villalon, Pedro Cuenca, Luis Orozco-Barbosa,”Limitation and Capabilities of

Qos Support in IEEE 802.11 WLANS”, IEEE, 2005.

[45] Qiang Ni, “Performance Analysis and Enhancements for IEEE 802.11e Wireless

Networks”, IEEE Network • July/August 2005

[46] Su-Jin Kwag, Sang-Sun Lee,” Performance Evaluation of IEEE 802.11 Ad-hoc

Network in Vehicle to Vehicle Communication”, ACM, 3rd International Conference on

Mobile Technology, Applications and Systems — Mobility 2006.

[47] Mohammad M. Rashid, Ekram Hossain, Vijay K. Bhargava,”Queueing Analysis of

802.11e HCCA with Variable Bit Rate Traffic”, 2006 IEEE

[48] Timo Kosch, Christian J. Adler, Stephan Eichler, Christoph Schroth, and Markus

Strassberger ,” the scalability problem of vehicular ad hoc networks and how to solve it”,

IEEE Wireless Communications , October 2006.

[49] D. Johnson, D. Maltz, and Y. Hu, “The dynamic source routing protocol for mobile

ad hoc networks,” April 2003, internet Draft: draft-ietf-manetdsr-09.txt.

[50] C. Perkins, E. Belding-Royer, and S. Das, “Ad hoc on demand distance vector

(AODV) routing,” July 2003, request for Comments 3561.

[51] Z. Haas, “A new routing protocol for reconfigurable wireless networks,” in

Proceedings of the IEEE International Conference on Universal Personal

Communications (ICUPC 1997), Oct. 1997.

References


[52] Y. Ko and N. Vaidya, “Location-aided routing (LAR) in mobile ad hoc networks,”

in Proceedings of the ACM/IEEE International Conference on Mobile Computing and

Networking (MOBICOM’98), 1998.

[53] Brad Williams and Tracy Camp,”Comparison of Broadcasting Techniques for

Mobile Ad Hoc Networks”, ACM MOBIHOC, 2002.

[54] S-Y. Ni, Y-C Tseng, Y-S Chen and J-P Sheu, “The broadcast storm problem in

mobile ad hoc networks”, Proc. ACM MobiCom ’99, Seatle, USA, Aug. 1999.

[55] Hao Zhang, Zhong-Ping Jiang, “Performance Analysis of Broadcasting Schemes in

Mobile Ad Hoc Networks”, IEEE 2004.

[56] Brad Williams, Dinesh P. Mehta, Tracy Camp and William Navidi, “Predictive

Models to Rebroadcast in Mobile Ad Hoc Networks”, IEEE Transactions on Mobile

Computing, vol. 3, no. 3, july-september 2004.

[57] Alpar Juttner, Adam Magi,”Tree Based Broadcast in Ad Hoc Networks”, Springer

Netherlands.2005.

[58] Demetres Kouvatsos, Is-Haka Mkwawa,” Broadcasting Methods in Mobile Ad Hoc

Networks: An Overview”, 2005.

[59] Joon Yoo, Hong-ryeol Gil, Chong-kwon Kim,” INK: Implicit Neighbor Knowledge

Routing in Ad Hoc Networks”, IEEE 2003.

[60] Gokhan Korkmaz, Eylem Ekici, “Urban MultiHop Broadcast Protocol for

InterVehicle Communication Systems”, ACM VANET’04, October 1, 2004,USA

[61] Dragos¸ Niculescu and Badri Nath, “Trajectory Based Forwarding and Its

Applications”, ACM MobiCom’03, Sept 14–19, 2003, San Diego, California, USA.

References


[62] Pai-Hsiang H siao and Jingyi Huang “Geographical Region Summary Service for

Wireless Routing”, CS223 Final Project Report.

[63] Daniele Miorandi,Lidia Yamamoto, Paolo Dini, “Service Evolution in Bio-Inspired

Communication Systems”, International Conference on Self-Organization and

Autonomous Systems in Computing and Communications (SOAS 2006),Sept 2006.

[64] Tatsuaki Osafune, Lan Lin, Massimiliano Lenardi,” Multi-Hop Vehicular Broadcast

(MHVB)”, 6th International Conference on ITS Telecommunication, 2006.

[65] Nathan Balon, Jinhua Guo, “Increasing Broadcast Reliability in Vehicular

AdHocNetworks”,ACM, VANET’06, Sept 29, 2006, Los Angeles, California, USA

[66] Sheela T and Raja J, Maximization of throughput by effective queue management

scheme for high speed network. Indian J. Sci. Technol. 2 (3), 28-31. Domain site:

http://www.indjst.org.

[67] Luca Campelli, Matteo Cesana, Roberta Fracchia, “Directional Broadcast

Forwarding of Alarm Messages in VANETs”,IEEE, 2007

[68] Jason LeBrun, Chen-Nee Chuah, Dipak Ghosal, Michael Zhang, “Knowledge-Based

Opportunistic Forwarding in Vehicular Wireless Ad Hoc Networks”, IEEE, 2005.

[69] Yu Chen and Jennifer L. Welch, “Location based Broadcasting for Dense Mobile Ad

Hoc Networks”, ACM, MSWiM'05, October 10-13, 2005

[70] Stefan Pleisch, Mahesh Balakrishnan, Ken Birman, “MISTRAL: Efficient Flooding

in Mobile Adhoc Networks”, ACM, MobiHoc’06, Italy, May 22–25, 2006

[71] Mun J. Lok, Bilal R. Qazi and Jaafar M. H. Elmirghani, Characterisation of Data

Dissemination in Vehicular Ad Hoc Networks in a City Environment,ACM, IWCMC’09,

Germany, June 21–24, 2009.

References


[72] C. Hernandez-Goya, P. Caballero-Gil, J. Molina-Gil and C. Caballero-Gil,

Cooperation Requirements for Packet Forwarding in Vehicular Ad-Hoc Networks

(VANETs), International Conference on Computer Systems and Technologies

CompSysTech’09.

[73] Ozan K. Tonguz, Nawaporn Wisitpongphan, Fan Bai,” DV-CAST: A Distributed

Vehicular Broadcast Protocol For Vehicular Ad Hoc Networks”, IEEE Wireless

Communications • April 2010

[74] Anthony Busson, “Performance Evaluation of Broadcast Protocols in VANET:

Point Process Approach”, ACM, PE-WASUN’09, Spain, October 28–29, 2009.

[75] Michael Slavik, Imad Mahgoub,” Stochastic Broadcast for VANET”, IEEE CCNC

proceedings, 2010.

[76] Houda Labiod, Nedal Ababneh, Miguel García de la Fuente, “An Efficient Scalable

Trajectory Based Forwarding Scheme for VANETs”, 24th IEEE International Conference

on Advanced Information Networking and Applications,2010

[77] Ming Li and Wenjing Lou, KaiZeng,” OppCast: Opportunistic Broadcast of

Warning Messages in VANETs with Unreliable Links”, IEEE, 2009

[78] Subir Biswas, Jelena Misic,” Proxy Signature-based RSU Message Broadcasting in

VANETs”, 25th Biennial Symposium on Communications,IEEE, 2010

[79] Anis Laouiti, Paul Muhlethaler, Yasser Toor, Reliable Opportunistic Broadcast in

VANETs (R-OB-VAN),IEEE, 2009

[80] Aneel Rahim, Imran Ahmad, Zeeshan Shafi Khan, Muhammad Sher, “A Survey On

Broadcast Approaches in VANETs”, Mosharaka International conference on

communication and network, Jordan 2008.

References


[81] S. Eichler, C. Schroth, T. Kosch, and M. Strassberger, “Strategies for context-

adaptive message dissemination in vehicular ad hoc networks,” e Second International

Workshop on Vehicle-to- Vehicle Communications, July 2006.

[82] Christoph Schroth, Robert Eigner, Stephan Eichler, Markus Strassberger, ”A

Framework for Network Utility Maximization in VANETs”,ACM, International

Conference on Mobile Computing and Networking, USA,September 29, 2006

[83] Lars C. Wolf, Carsten Griwodz, Ralf Steinmetz, “Multimedia Communication”,

Proceedings of the IEEE, vol. 85, no. 12, December 1997

[84] Jyh-Ren Jerry Shieh “On the Security of Multimedia Video Information”,IEEE,2003

[85] Honggang Wang, Michael Hempel, Dongming Peng,Wei Wang, Hamid Sharif,

Hsiao-Hwa Chen, “Index-Based Selective Audio Encryption for Wireless Multimedia

Sensor Networks”, IEEE Transactions On Multimedia, vol. 12, no. 3, April 2010,

[86] Klara Nahrstedt, Jana Dittmnn, Petra Wohlmacher, “Approaches to Multimedia and

Security” IEEE , IEEE International Conference on Multimedia and Expo, ICME 2000.

[87] M. Raya, P. Papadimitratos,J.-P. Hubaux, Securing Vehicular Communications, In

IEEE Wireless Communications Magazine, Special Issue on Inter-Vehicular

Communications, October 2006.

[88] Yung-Cheng Chua, Nen-Fu Huang,” Delivering of Live Video Streaming for

Vehicular Communication Using Peer-to-Peer Approach, IEEE, 2007

[89] Shiwen Mao, Shunan Lin, Shivendra S. Panwar, Yao Wang, Emre Celebi, “Video

Transport Over Ad Hoc Networks: Multistream Coding With Multipath Transport”,

IEEE Journal on Selected Areas in Communications, vol. 21, no. 10, December 2003

References


[90] Pau Arce, Juan C. Guerri, Ana Pajares, Oscar Lázaro,” Performance Evaluation of

Video Streaming Over Ad Hoc Networks Using Flat and Hierarchical Routing

Protocols”, Springer Mobile Netw Appl (2008) 13:324–336

[91] Stephen Smaldone, Lu Han, Pravin Shankar, and Liviu Iftode,” RoadSpeak:

Enabling Voice Chat on Roadways using Vehicular Social Networks”, ACM,

SocialNets’08, April 1, 2008, UK

[92] Fabio Soldo, Claudio Casetti, Carla-Fabiana Chiasserini, Pedro Chaparro,”

Streaming Media Distribution in VANETs”, IEEE "Globecom" 2008

[93] Maurizio A. Bonuccelli, Gaetano Giunta , Francesca Lonetti, Francesca Martelli,”

Real-time video transmission in vehicular networks”,IEEE,2007

[94] Junwen Mi, Fuqiang Liu, Shangzhi Xu, Qi Li,” A Novel Queue Priority Algorithm

for Real-time Message in VANETs”, International Conference on Intelligent

Computation Technology and Automation, IEEE, 2008.

[95] Paolo Bucciol, Federico Ridolfo and Juan Carlos De Martin,” Multicast Voice

Transmission over Vehicular Ad Hoc Networks: Issues and Challenges”, Seventh

International Conference on Networking, IEEE, 2008.

[96] Maxim Raya and JeanPierre Hubaux,” The Security of Vehicular Ad Hoc

Networks”ACM, SASN’05, November 7, 2005

[97] Philippe Golle, Dan Greene, Jessica Staddon, “Detecting and Correcting Malicious

Data in VANETs” ACM, USA, VANET’04, October 1, 2004.

[98] Bin Xiao, Bo Yu, Chuanshan Gao, “Detection and Localization of Sybil Nodes in

VANETs”, DIWANS’06, ACM, USA September 25, 2006.

References


[99] Maxim Raya, Panagiotis Papadimitratos, Imad Aad, Daniel Jungels, Jean-Pierre

Hubaux “Eviction of Misbehaving and Faulty Nodes in Vehicular Networks”, IEEE

Journal on Selected Areas in Communications,2007.

[100] Jose Santa, Manabu Tsukadat, Thierry Emstt, Antonio F. G6mez-Skarmeta,”

Experimental Analysis of Multi-hop Routing in Vehicular Ad-hoc Networks”,

International Journal of Internet Protocol Technology, Vol 4 , Issue 3 Sept 2009.

[101] Carolina Pinart, Iván Lequerica, Isaac Barona, “DRIVE: a reconfigurable testbed

for advanced vehicular services and communications”, Tridentcom, March 18–20, 2008.

[102] Ali Tufail, Mike Fraser, Ali Hammad, Kim Ki Hyung, Seung-Wha Yoo,” An

Empirical Study to Analyze the Feasibility of WIFI for VANETs”,IEEE, 2008

[103] Peter Lerchbaumer, Alejandro Ochoa, Elisabeth Uhlemann, “Test Environment

Design for WirelessVehicle Communications”, IEEE, 2007

[104] Karim Seada,”Insights from a Freeway Car-to-Car Real-World Experiment”, ACM,

WinTech’08, September 19, 2008.

[105] http://ivc.epfl.ch/, 24 Feb 2008

[106] Francisco J. Martinez1, Chai Keong Toh, Juan-Carlos Cano, Carlos T.

Calafate,PietroManzoni, “A survey and comparative study of simulators for vehicular

adhoc networks (VANETs)” , Wirel. Commun. Mob. Comput. 2009.

Documents

SECURE DATA DISSEMINATION SCHEME FOR VEHICULAR AD …