emergency information dissemination in vehicular ad hoc

Emergency Information Disseminationin

Vehicular Ad Hoc Networks

A thesis submitted in partial fulfillment of the requirementsfor the degree of

Master of Technology (Honours)

in

Computer Science and Engineering

by

Rayman Preet Singh

06CS3023

advised by

Dr. Arobinda Gupta

Department of Computer Science and EngineeringIndian Institute of Technology, Kharagpur

May 2011

Certificate

This is to certify that the thesis entitled Emergency Information Dis-

semination in Vehicular Ad Hoc Networks submitted by Rayman Preet

Singh (06CS3023) to the Department of Computer Science and Engineering

is a bona fide record of research work carried out by him under my supervi-

sion and guidance. This thesis has fulfilled all the requirements as per the

regulations of the institute and, in my opinion, has reached the standard

needed for submission.

Dr. Arobinda Gupta

Professor

Department of Computer Science and Engineering

IIT Kharagpur

May 2011

Acknowledgment

I would like to express my gratitude towards Prof. Arobinda Gupta for

the supervisory role he played to utmost perfection. Taking time out of his

busy schedule, he ensured that the project work was carried out methodically

and meticulously. I especially thank him for his encouragement and his

accurate comments which were of critical importance, and am indebted to

him for extending out all the necessary support throughout the duration of

the project and for being a constant source of inspiration.

I would also like to thank my parents, S. Joga Singh and Narinderjit Kaur,

and friends, Sayantan Ghosh and Anirudha Patro for their invaluable help,

guidance and motivation. Their continuous support and encouragement has

played a key role in the completion of this work.

Rayman Preet Singh

06CS3023

Department of Computer Science and Engineering

IIT Kharagpur

May 2011

Abstract

The main goal of inter-vehicle communication technology is to provide

the drivers with more information regarding the surroundings than they can

visually perceive. A Vehicular Ad-Hoc Network, or VANET, is one such tech-

nology that uses moving vehicles as nodes in a network to create a wireless

ad hoc network. Many applications in VANETs are based on dissemination

of information to the drivers about hazardous situations and can help avoid

potential dangers. Such applications require that the information is delivered

to all vehicles which are within a certain area and is retained in that area

for a certain period of time. Most of the existing information dissemination

protocols for VANETs do not provide this much needed retention of infor-

mation and little research has been done in this regard. Stored Geocast, is an

information dissemination protocol which provides a retention of information

within a pre-determined area of the road. However, the overhead incurred

by it is large and makes it unsuitable for deployment over VANETs.

In this thesis, we propose an information dissemination protocol which

provides both a spatial and temporal retention of information and incurs

less overhead. Experimental results are used to draw a comparison between

the performance of the existing information dissemination protocols. Per-

formance of the proposed algorithm is evaluated and compared with Stored

Geocast and other existing information dissemination protocols.

Contents

Contents i

1 Introduction 1

1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.3 Thesis Overview . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2 Background and Literature Overview 6

2.1 Existing Protocols for Information Dissemination . . . . . . . 7

2.1.1 Contention Based Approach . . . . . . . . . . . . . . . 8

2.1.2 Improvements over Contention Based Approach . . . . 9

2.1.3 Congestion Based Approach . . . . . . . . . . . . . . . 10

2.2 Stored Geocast . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.3 Problems with Existing Approaches . . . . . . . . . . . . . . . 13

3 Zone Based Forwarding 15

3.1 Overview of Proposed Strategy . . . . . . . . . . . . . . . . . 15

3.2 Description of the Algorithm . . . . . . . . . . . . . . . . . . . 17

3.3 Pseudocode of the Algorithm . . . . . . . . . . . . . . . . . . 18

i

3.4 An Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

3.5 Overcoming Network Congestion . . . . . . . . . . . . . . . . 23

4 Experimental Study 26

4.1 Simulation Setup . . . . . . . . . . . . . . . . . . . . . . . . . 26

4.2 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . 28

4.3 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

4.3.1 Comparison of Existing Approaches . . . . . . . . . . . 29

4.3.2 Performance Evaluation of ZBF . . . . . . . . . . . . . 32

4.3.3 Performance Evaluation of ZBF Extension . . . . . . . 38

5 Conclusion 41

5.1 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

ii

List of Figures

3.1 Method invoked by vehicle i for initializing or relaying the

dissemination . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

3.2 Method invoked at vehicle i on receipt of a Query message . . 20

3.3 Method invoked at vehicle i for broadcast of an Info message . 20

3.4 Method invoked at vehicle i on receipt of a Reply message . . 21

3.5 Method invoked at vehicle i on receipt of an Info message . . . 21

3.6 Sample scenario with vehicle i as initiating vehicle. Blocks de-

pict the vehicles and arrowheads denote their direction(North/South)

of movement. vehicle i (solid block) initiates the dissemination. 22

3.7 Method invoked at vehicle i on receipt of an Info message . . . 24

3.8 Method invoked at vehicle i on non receipt of a Query message

due to message drop . . . . . . . . . . . . . . . . . . . . . . . 25

4.1 Comparative performance evaluation of existing strategies :

Number of Vehicles Informed (Coverage) . . . . . . . . . . . . 29

4.2 Comparative performance evaluation of existing strategies :

Number of Messages Broadcasts . . . . . . . . . . . . . . . . . 30

4.3 Performance of the strategy proposed by Fathy and Khakbaz

in [3]. Information spreads to all vehicles as time progresses,

starting at t=170 . . . . . . . . . . . . . . . . . . . . . . . . . 31

iii

4.4 Total number of vehicles informed v/s Frequency (f) of peri-

odic broadcast. . . . . . . . . . . . . . . . . . . . . . . . . . . 33

4.5 Total number of messages broadcast v/s Frequency (f) of pe-

riodic broadcast. . . . . . . . . . . . . . . . . . . . . . . . . . 34

4.6 Distribution of different types of messages broadcast v/s Fre-

quency(f) of periodic broadcast. . . . . . . . . . . . . . . . . . 35

4.7 Distance inside a zone which a vehicle traversed before being

informed v/s Frequency(f) of periodic broadcast. . . . . . . . . 36

4.8 Total number of messages broadcast per informed vehicles v/s

Frequency(f) of periodic broadcast. . . . . . . . . . . . . . . . 37

4.9 Result of the Fathy algorithm [3] on a sample highway scenario. 38

4.10 Number of vehicles reached v/s Frequency(f) of periodic broad-

cast. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

4.11 Total number of messages broadcast v/s Frequency(f) of peri-

odic broadcast. . . . . . . . . . . . . . . . . . . . . . . . . . . 40

iv

Chapter 1

Introduction

A Mobile Ad Hoc Network, or MANET, is a wireless network consisting of

mobile nodes in which all the network-level activity is carried out by the

nodes themselves, without additional infrastructure support. Each node in

such a network plays the role of a router as well as an end-machine, and

hence, all nodes in the network participate actively in message forwarding.

The network topology is subject to change owing to the mobility of the nodes.

A Vehicular Ad-Hoc Network, or VANET, is a special kind of MANET

in which mobile nodes are all vehicles equipped with an On-Board Unit

(OBU) that enables them to send and receive messages to and from each

other. Additionally, a VANET might also interface with communication

points provided by on-road infrastructure, commonly termed as Road-side

Units (RSUs).

Several applications have been proposed for VANETs. Bai et al. [4]

survey these applications and divide them into following categories:

1. Safety applications, in which VANET is used to identify scenarios

that could potentially endanger the vehicle drivers’ safety. For instance,

drivers could benefit from real-time alerts about accidents happening in

their vicinity. Road Hazard Condition Notification (RHCN) is a safety

application in which a vehicle detecting a road hazard (e.g. fluid, ice)

1

Chapter 1: Introduction

notifies vehicles within the potentially affected region. Likewise, Emer-

gency Electronic Brake Light (EEBL) is a safety application in which

a vehicle braking hard notifies vehicles in its neighborhood. Other

examples of safety applications in VANETs include, Road Feature No-

tification (RFN) [4], Cooperative Collision Warning (CCW) [5] and

Cooperative Violation Warning (CVW) [7]. Note that, in each of these

applications some form of warning is emitted on the occurrence of a

designated event associated with the warning.

2. Convenience and commercial applications, in which OBUs com-

municate with each other in order to provide the driver such services

as traffic congestion and flow information, parking availability informa-

tion, automatic toll payment etc. Traffic congestion information can

be propagated amongst vehicles and can be used for producing a more

fluid traffic on roads and avoiding traffic jams. Commercial applica-

tions in VANETs include internet access, streaming audio and video

etc.

In this thesis, we shall be addressing the problem of designing the under-

lying strategy which needs to be in place to spread the warning information

associated with different safety applications. Traditionally, information dis-

semination in VANETs is achieved by means of a flooding mechanism, and

vehicles undertake subsequent re-broadcasts to overcome network fragmenta-

tion. However, the information in which a given vehicle might be interested,

is dependent on its current physical location, and hence an indiscriminate

propagation of information does not suffice for the needs of most VANET

applications designed for this purpose.

1.1 Motivation

The process of information dissemination is initiated on the occurrence of

an emergency event, and has associated with it a protocol for sending and

2


receiving messages used to spread the warning information. An efficient

dissemination process should possess the following characteristics :

1. Maximum coverage across relevant vehicles: Any warning infor-

mation usually has a specified area of interest and a fixed time period

within the limits of which it is considered valid and usable by the drivers

receiving it. These are referred to as the effect area and effect time of

the warning information. For instance, warning information about a

slippery road has an effect area equal to the segment of road on which

the road is slippery and effect time equal to a certain estimated fixed

time duration for which the slipperiness will last. Thus, in order to be

effective any warning information dissemination strategy should guar-

antee the delivery of information to all vehicles lying within the effect

area and effect time.

2. Minimum latency: Since warning information is directly linked to

the safety of the drivers on the road, the time difference between the

actual occurrence of the event and the receipt of the associated warning

information is desired to be as small as possible. Hence, a warning

information dissemination strategy is required to minimize the latency

of dissemination.

3. Low overhead: In addition to latency, the efficiency of an information

dissemination protocol is also governed by the amount of data other

than the warning information, which it sends over the wireless ad-hoc

network. An indiscriminate flooding can cause the channels to get

jammed and cause packet drops.

Imposing a restriction on dissemination of information beyond the effect

area will also stop transmission of warning information to vehicles for which

it is of little significance. This reduces wastage of bandwidth over the wireless

channel and improves channel availability.

Several schemes have been proposed and employed for propagating infor-

mation in VANETs [2] [3] [9] [12] [10]. They aim to spread the information to

3


as many number of vehicles as possible. This leads to the information being

disseminated in a large area which often includes the effect area. However, a

retention of information in the effect area is not maintained. Due to this ab-

sence of retention, vehicles coming into the effect area after the propagation

of information has ceased, do not get the warning information.

Little research has been done on designing information dissemination pro-

tocols which provide retention of information. Stored Geocast [10] is an in-

formation dissemination protocol for VANETs which provides a retention of

information in the effect area. However, the overhead incurred by it is large

and makes it unsuitable for deployment over VANETs. Thus, an information

dissemination protocol for VANETs which provides both retention of infor-

mation in its effect area during the duration of its effect time and incurs less

overhead is needed. If such a information dissemination protocol is available

then it can be used by VANET applications such as RHCN and RFN to effi-

ciently retain the information within the effect area of the event and deliver

it to incoming vehicles.

1.2 Contributions

In this thesis we first present a detailed analysis of the existing information

dissemination protocols in VANETs. We identify that most of the dissemi-

nation existing protocols do not retain the warning information within the

effect area for the duration of the effect time. This is a crucial requirement

for designing safety applications for VANETs. However, Stored Geocast [10]

fulfills this requirement but incurs large overhead. We propose an efficient

information dissemination strategy which incurs small overhead and is capa-

ble of retaining the information within the effect area for the entire duration

of the effect time. The strategy is formalized as an algorithm and analytical

results quantifying its performance are presented.

We use experimental results to draw a comparison between the perfor-

mance of the existing dissemination strategies. Further, we evaluate the

4


performance of the proposed algorithm and compare its performance with

Stored Geocast [10] and other existing information dissemination protocols.

1.3 Thesis Overview

The thesis is further organized as follows :

• Chapter 2 presents a survey of related research work on informa-

tion dissemination in VANETs. Some background and essential no-

tions related to our work are also incorporated. Finally, an analysis

of the shortcomings of existing information dissemination protocols in

VANETs is presented.

• Chapter 3 discusses the proposed strategy for information dissemina-

tion in VANETs. We formally describe our proposed algorithm, along

with a discussion and a sample run on a sample scenario. The chapter

ends with the description of a proposed extension of our algorithm,

which counters network congestion if present.

• Chapter 4 describes the system setup employed for simulation and

performance evaluation of various information dissemination strategies.

We describe, in detail, the measures we have adopted to evaluate the

performance evaluation. Further, an evaluation of the relative per-

formance of the existing approaches for information dissemination is

presented, followed by a performance evaluation of the proposed algo-

rithm. Finally, we analyze the performance of our proposed approach

and comment on its performance in relation to other dissemination

strategies in its class.

• Chapter 5 summarizes the contributions of this thesis, and identifies

possible directions for future research.

5

Chapter 2

Background and Literature

Overview

The mode of communication in VANETs involves broadcast of messages on

the 5.9Ghz frequency band licensed for VANET applications. We assume

that these broadcast messages are delivered in single-hop, using IEEE 802.11p

(or Dedicated Short Range Communications, DSRC) technology pursued by

industry and governments [13].

In VANETs, there are two types of transmission carried out by the ve-

hicles: event-driven messages, whose transmission takes place on the occur-

rence of certain well-defined events, such as the transmission of safety mes-

sages, and periodic transmissions called beacons used for providing mutual

awareness. Hence, a broadcast of a message containing warning informa-

tion is an event-driven message since it is triggered by the occurrence of a

hazardous situation. Note that, warning information messages may also be

re-broadcast periodically for dissemination. Slow Vehicle Advisory (SVA),

Road Hazard Condition Notification (RHCN), and Emergency Electronic

Brake Light (EEBL) described in [4] are some examples of event-driven mes-

sages that are transmitted by vehicles, which are used for ensuring safety

of vehicles and also for better coordination among vehicles. A SVA alert

is broadcast by a vehicle that suddenly slows down or stops on the road,

6

Chapter 2. Background and Literature Overview

enabling the recipients to take evasive action. A RHCN alert is broadcast

by a vehicle that observes a possibly hazardous condition on the road, such

as road slipperiness, to warn other vehicles about this condition. An EEBL

alert is broadcast by a vehicle which is braking hard, to enable the recipients

to take evasive action. However, certain convenience applications such as

Congested Road Notification (CRN) also employ event-driven messages. A

beacon message is a periodic message broadcast by a vehicle and contains its

positional information, speed and direction at the time of broadcast.

In the following section, we first provide a brief insight into the existing

information dissemination protocols in VANETs. We then look at one of the

existing protocols, Stored Geocast in more detail as it is the protocol that is

of most relevance to the work presented in this thesis. We end this chapter by

stating the shortcomings present in the existing approaches for information

dissemination, which forms the motivation for our proposed algorithm in the

next chapter.

2.1 Existing Protocols for Information Dis-

semination

In the classical flooding protocol [1], the initiating vehicle starts the dis-

semination by sending the information messages to all of its neighbors, and

any vehicle receiving the message broadcast re-broadcasts exactly once. In

addition to this, the vehicles periodically rebroadcast the message in order

to overcome network fragmentation. This flooding strategy causes a lot of

redundant broadcasts as well as redundancy in message delivery. Several

strategies have been suggested that improve upon this simple flooding strat-

egy.

7


2.1.1 Contention Based Approach

Torrent-Moreno [2] presents a strategy where one vehicle initiates the dis-

semination by broadcasting the information. This strategy employs a con-

tention mechanism to select intermediate vehicles (forwarders) which will

re-broadcast the message so as to carry forward the propagation. The vehi-

cles receiving the message decide by means of a waiting period, as to which

one must forward the message.

Each vehicle receiving the message first computes its distance (in meters)

from the sender, and is referred to as the progress (denoted as P ) of the

vehicle. Each vehicle then assigns itself a waiting time (denoted as t(P ))

according to the following rules :

t(P ) =

∞ if P > rCA

T ′.(1− P

rCA

) if rCA ≥ P ≥ 0m

∞ if P < 0m

where T ′ is the maximum waiting time; and rCA fixes the radius of the area

where potential forwarders must be located, and is typically equal to the

transmission range R of the vehicles (assumed equal for all vehicles). There-

fore, of all the vehicles that received the sender’s broadcast, the vehicle at

the largest distance (P ) from the sender vehicle will select the shortest wait-

ing time, after which it will re-broadcast the information so as to propagate

it. Upon reception of the re-broadcast message, vehicles which are still con-

tending will cancel their contention process. The vehicles which receive the

warning information for the first time via this re-broadcast then repeat the

contention process to carry forward the propagation.

Note that this approach is vulnerable to a partitioned network and fails

to propagate the information in the presence of network partitions across the

VANET. The broadcasting vehicle does not detect whether a new intermedi-

ate vehicle (forwarder) has been selected by the contention process or not. In

the absence of a forwarding vehicle, the propagation stops at the boundary

8


of that connected component of the VANET containing the vehicle initiating

the dissemination process.

2.1.2 Improvements over Contention Based Approach

A more reliable method for disseminating safety information is presented by

Fathy and Khakbaz in [3]. They employ the Torrent-Moreno [2] contention

based approach (with rCA = R) for propagation of information, but propose

certain improvements so as to improve upon its shortcomings. Between-

ness conditions proposed by them aim to ensure that during the contention

process, of all the vehicles that receive a re-forwarded message from the re-

broadcasting (farthest) vehicle, only the vehicles present between the actual

sender and the re-broadcasting vehicle cancel their contention process on re-

ceipt of the re-broadcast message. This is important because in case the

re-broadcasting (farthest) vehicle has a progress P less than rCA, vehicles on

the opposite side of the sender can cancel their contention on receiving the

rebroadcast.

Additionally, they also propose a connectivity hole detection method. If

the last broadcasting vehicle does not receive a re-broadcast from one of the

vehicles in the contention process within a fixed time interval, a connection

hole is deemed to be detected. After detection of a connectivity hole, the

vehicle shall start sending small periodic hello messages which contain their

location and ID. Vehicles receiving hello messages reply by a similar message

containing their location and ID. If the vehicle receives a hello message that

shows the entrance of a vehicle in direction of dissemination, it will broadcast

the information message and by assigning the forwarding task to the new

entered vehicle, propagation is continued. The hello messages aim to bridge

the network fragments, so that whenever a vehicle travels to a new fragment

it can repeat the propagation by inducing Torrent-Moreno’s contention based

approach.

9


2.1.3 Congestion Based Approach

Many VANET applications assume that each vehicle knows its neighbors

through exchanging periodic beacon messages. By use of these periodic bea-

cons, vehicles can measure the level of vehicular congestion around them.

One such approach to measure vehicular congestion was proposed in [9], in

which the vehicles measure two kinds of vehicular congestion around them

: Instantaneous Congestion (IC), which is the instantaneous picture of the

traffic in the vicinity of a vehicle, and Stabilized Local Congestion (SLC),

comprising of the neighboring vehicles of a vehicle which have been stable

members of its instantaneous congestion over a period of time.

An information dissemination method based on vehicular congestion es-

timates was proposed in [9]. Each vehicle computes its instantaneous con-

gestion and stabilized local congestion using the period beacon messages. In

addition, each vehicle u possesses a measure (bcastu) which, on receipt of

an information message, is used to decide whether to re-broadcast or not as

follows :

bcastu = q |SLC||IC| + (1− q)bcastv, where q is a constant.

vehicle u re-broadcasts if and only if bcastu ≥ bcastTH . Any sender encloses

its bcast value in the information message that it sends, with the initial sender

using a value of 1. The parameter q provides for a weighted sum between

controlled flooding using the local congestion information, and the traditional

flooding strategy. The weighted flooding component drives the propagation

of information whereas the vehicular congestion estimates are used at the

vehicles to decide whether to re-broadcast the information or not. Hence,

a vehicle re-broadcasts the information only when most of the vehicles in

its immediate neighborhood are stable and in all probability will receive the

information. Additionally, a probabilistic broadcast based on the congestion

around a vehicle is also possible, where a vehicle with high congestion around

it broadcasts with a lower probability p, (and vice versa), as only few of the

vehicles need to broadcast in such an environment (p = 1|SLC|).

10


Yu and Heijenk in [12] propose a dissemination strategy which utilizes

the concept of ‘effect line’ and ‘safety line’ near an emergency event, but

their work is based on the assumption of a Poisson distribution model of

traffic volume and involves message broadcast by all vehicles with a dynamic

adjustment to inter-broadcast wait time. However, vehicular traffic has been

characterized to exist in three difference categories of Free Flowing, Wide

Moving Jams and Synchronized Flow, and hence is not liable to follow Pois-

son distribution over the number of vehicles as is assumed in this strategy.

2.2 Stored Geocast

The transmission of a message to some or all vehicles within a geo-graphical

area is referred to as a Geocast. A Stored Geocast is a time stable geocast,

which is delivered to all vehicles that are inside a destination region within

a certain period of time.

Manihofer et al. in [10] proposed an infrastructure-less approach based

on Stored Geocast. This would serve as a solution for location based services

in VANETs, like realizing a virtual traffic sign, which in turn is also a method

to achieve warning information dissemination. On detection of an emergency

event, the vehicles in a VANET can coordinate to setup such virtual traffic

signs which will relay the information to vehicular traffic which is inbound

to the area of interest.

In their proposed approach, Manihofer et al. in [10] propose to elect a

vehicle in the destination region of a geocast message to store information

messages. This dynamically elected vehicle within the destination region is

responsible for storing and delivering the message. A periodic broadcast or

notification-triggered broadcast is adopted for message delivery. A handover

of messages is done when this elected vehicle leaves the destination region

and a process to elect a new leader is started. However, to avoid frequent

handovers, Manihofer et al. suggest that it is desirable to choose one that

stays as long as possible in the destination region. Such a vehicle is charac-

11


terized by low velocity and closeness to the center of the destination region.

They propose the use of a leader election algorithm suggested in [11] as a

part of the GeoGRID protocol.

The leader election algorithm described by Liao et al. in the GeoGRID

[11] protocol divides the destination region into a set of 2-D grids and uses a

set of guidelines in order to elect a leader for each grid. Firstly, it is suggested

that the vehicle nearest to the physical center of a grid is to be elected as

the leader because such a host is more stable and more likely to remain in

its grid for a long time. Secondly, once a vehicle is elected as leader it will

remain so until it moves out of its grid.

When a vehicle moves closer to the physical center of the grid it will

not be elected as leader until the earlier one leaves the grid. Periodically,

the elected leader will broadcast its existence by sending a GATE(g,loc)

message, where g is its grid coordinate and loc is its current location. All the

other vehicles monitor the current leader in their grid and if a GATE(g,loc)

message is not received for a predefined time period, they will broadcast a

BID(g, loc) message, where g is the grid coordinate and loc is the vehicle’s

current location.

Upon the leader vehicle (if it is still in the grid) hearing the BID message,

it will reply with a GATE to reject the BID sender’s bid. Upon a non-leader

vehicle at a location closer to the physical center of the grid hearing the BID

message, it will reply with a BID(g, loc′) message to reject the former’s bid,

where loc′ is the sending vehicle’s current location. However, if no such

messages are received by the bidding vehicle for a predefined time period,

the bidding host will silently elect itself as the leader.

When a leader leaves its current grid, it broadcasts a RETIRE(g, T )

message where g is the grid coordinate where it served as a gateway. All

other vehicles on receiving a RETIRE message send BID messages in order

to elect a new leader. Lastly, to eliminate the possibility of having multiple

leaders in a grid, when a vehicle which assumes itself as a leader receives

a GATE message from another vehicle at a location closer to the physical

12


center of its grid, it silently changes itself to a non-leader vehicle without

sending any message. We shall refer to this algorithm as Stored Geocast

algorithm.

2.3 Problems with Existing Approaches

With regards to the existing information dissemination approaches discussed

in Section 2.1, we observe that they are all message-centric in nature and aim

to attain maximum coverage in terms of vehicles informed/are covered. How-

ever, emergency warning information in VANETs have a definite area (effect

area) associated with it, within the confine of which it is valid. Likewise,

there exists a time limit (effect time, measured from the start of dissemina-

tion), within the duration of which the emergency information holds valid.

Thus, it is imperative to produce persistence of the warning information in

its effect area for the duration of the effect time, rather than focusing ex-

haustively on achieving coverage. The approaches described in Section 2.1

spread the information to a majority of vehicles around the initiating vehi-

cle (or hazard), but this ignores the possibility, that an uninformed vehicle

visiting the area at a later instant of time (but within the effect time), will

still be deprived of the warning information. In order to ensure that warning

information reaches all vehicles, who are in the effect area at some point of

time within the effect time, repeated broadcast by some of the informed ve-

hicles is necessary. In addition, the congestion based approach assumes the

existence of underlying periodic beaconing by the vehicles, which increases

the network congestion.

Hence, a mechanism is needed which causes warning information to per-

sist in the effect area for the duration of the effect time. However, causing

all the informed vehicles to perform a periodic re-broadcast will amount to

large number of broadcasts and redundancy. Note that, a periodic broadcast

by one vehicle with a transmission range R will ensure the persistence of

information within a road segment of length R.

13


As described in Section 2.2, Manihofer et al. in [10] suggest that a vehicle

that stays in the destination region for as long as possible is to be elected

as the leader, and propose the use of GeoGRID [11] as the leader election

algorithm. However, GeoGRID is a grid based approach, based on electing

the vehicle closest to the center of a region (grid box) as the leader. But

in a VANET scenario, the amount of time a vehicle spends in a particular

region is dependent upon factors like velocity, acceleration, driver behavior

and traffic congestion. Thus, for its use in VANETs, a leader election algo-

rithm which addresses these needs should be employed. Secondly, GeoGRID

employs periodic GRID and BID messages, which add to the overhead, as

warning message dissemination is to be carried out only when an emergency

event occurs and not at all times. Hence, in order to disseminate warning

information with a nominal overhead, a reactive protocol is needed rather

than a proactive one.

Finally, an exhaustive simulation and testing of the existing dissemination

strategies in the context of VANETs would have provided justification for the

use of Stored Geocast in VANETs, which has not been addressed in [10] and

[11].

14

Chapter 3

Zone Based Forwarding

In this chapter, we propose a strategy for information dissemination which

overcomes the shortcomings of the existing approaches, as identified in Sec-

tion 2.3. In the following sections, we first present a brief overview of the

proposed approach followed by a formal description of the algorithm and an

example run on a sample scenario. We end this chapter by presenting an

extension of the algorithm which overcomes network congestion encountered

during the dissemination process.

3.1 Overview of Proposed Strategy

Apart from assuming that the transmission range for all vehicles is the same

and equal to R, we make the following assumptions:

• Roads have two-way traffic with lower and upper speed limits as 0 and

vMAX respectively.

• Message propagation delay is negligible in comparison to time required

for a considerable kinematic motion.

• At any vehicle i, its current position (Pi), velocity (vi), acceleration

(ai) and direction of motion (d̂i) are available.

15

Chapter 3. Zone Based Forwarding

• Warning message propagation begins with exactly one vehicle broad-

casting the first warning message.

A periodic broadcast of a message by a vehicle while traveling a distance

R, guarantees the delivery of the message to all vehicles which are present

on that road segment of length R. This guarantee is dependent upon the

frequency (f) of the periodic broadcast. Our strategy involves dividing the

entire effect area of the warning information into segments of length R, each

of which is referred to as a zone. We assign one vehicle in each zone the task

of periodically broadcasting the warning information to notify other vehicles

in that zone. This vehicle is referred to as a forwarder for that zone. For

each zone, the vehicle that spends the longest time in the zone is elected

to be the forwarder. Whenever a forwarder exits a zone a new forwarder is

elected from amongst the vehicles present in the zone and the task of periodic

broadcasting is then handed over to the new forwarder. At the end of the

effect time duration all forwarders stop their periodic broadcast.

Table 3.1 shows the three three kinds of messages employed. The Info

message is used by the forwarder for periodic broadcast. It contains all the

details about the particular warning information and its effect area and effect

time. The Info message also contains the forwarder’s position, direction of

motion and ID. The Query and Reply messages are used for electing a new

forwarder when a forwarder leaves its zone. In addition to the contents of

the Info message, these messages contain a type.

Any vehicle is always in one of three modes {Receive, Forward, Relay}and performs functions accordingly. The Forward mode signifies that the

Message Type ContentInfo Warning Information Content, Effect Time, Effect Area,

Sender position, Sender Direction, Sender IDQuery Info, QueryReply Info, Reply

Table 3.1: Message forms.

16


vehicle is a forwarder. Whenever a forwarder leaves a zone and has to elect

a new forwarder it changes its mode to Relay. All other vehicles, which are

also the recipients of the periodic Info messages are in Receive mode.

3.2 Description of the Algorithm

Before start of dissemination all vehicles are in Receive mode. A vehicle i

initiating the dissemination changes its mode to Relay, broadcasts a Query

message and waits for T time for receiving a Reply message. Any vehicle j

at position Pj, on receiving the Query message, computes distance s which it

needs to travel to reach the current position (Pi) of the sender if it is headed

towards it. In case it is headed away from Pi, s is the distance it needs to

travel to reach the boundary of i’s transmission range (R). Using vj, aj,

and d̂j vehicle j computes the time ts it will take to travel the distance s.

Since a Query message is always broadcast by a forwarder exiting a zone, the

distance s can be computed as follows:

s =

|Pj − Pi| if d̂i = d̂j

R− |Pj − Pi| if d̂i = −d̂j.

Vehicle j then computes time ts which it will take to travel the distance s.

Time ts is computed as

ts =s

vj

where vj is the current speed of vehicle j. Time ts can also be computed as√u2 + ai.s− u

aifor more accuracy. Since our aim is just to estimate which

vehicle will be present in a zone for the longest duration, we prefer to use

(s

vj) for simplicity.

Vehicle j then waits for a time twait, computed using ts, such that twait ∝1

tsand twait ∈ [0, T ]. Time twait is calculated as the maximum of

N

tsand

T , where N is a suitable normalizing factor. After expiration of the twait

period vehicle j broadcasts a Reply message. However, if a Reply message,

17


broadcast from another vehicle, is received during the wait period (twait),

vehicle j cancels its transmission of the Reply message contingent upon the

condition that both vehicle j and the vehicle sending the Reply message are

on the same side of the vehicle which sent the Query message. The vehicle

k which sends a Reply message becomes a forwarder (changes to Forward

mode). The road segment of width R between Pi and i’s transmission range

boundary is the zone for this forwarder. On becoming the forwarder, vehicle

k records its current position Pk as RECXY in order to compute the zone

boundaries.

The forwarder k uses RECXY to detect when it reaches the zone border,

at which point it broadcasts a Query message. As described earlier, of all the

vehicles in the zone, the one whose twait expires first sends a Reply message

and gets elected as the new forwarder for the zone. The task of periodic

rebroadcast of Info messages is hence, handed over to the new forwarder.

Note that, a Query message is always broadcast by a forwarder which is

at either zone boundary and is heading out of the zone. Also, if a forwarder

fails to find a new forwarder at the time of exiting the zone, it repeats the

process to find a forwarder at a later instant, until which it remains the

forwarder (and retains its mode).

The frequency of periodic re-transmissions of Info messages f , is upper

bounded byvMAX

R. Wait time T is empirically selected such that T > 2 ×

(message propagation delay). Message propagation delay is a characteristic

of the medium and is typically in the range [10,15] ms.

3.3 Pseudocode of the Algorithm

Figure 3.1 shows the pseudocode for INITIALIZE, the method invoked at the

time of initialization of dissemination. INITIALIZE is also invoked when a

forwarder leaves a zone and a new forwarder is to be elected. In this method,

vehicle i broadcasts a Query message and waits for a Reply message for a

timeout period of T seconds. If a Reply message is not received, vehicle

18


Initialize(i)1 Mode← Relay2 Broadcast Query message3 Receive Reply message4 if Reply message not received within T sec

5 then Sleep(1

f)

6 Initialize(i)

Figure 3.1: Method invoked by vehicle i for initializing or relaying the dis-semination

i repeats the process of broadcasting a Query with frequency f . Hence,

vehicle i continues to be the forwarder until a new forwarder is found. Note

that, the Info message is contained in the Query message. Figure 3.2 shows

the pseudocode for RECEIVE-QUERY, the method invoked on receipt of a

Query message at a vehicle i. In this method, vehicle i computes its wait

time twait and waits for twait seconds before sending a Reply message, only if

no other Reply message is received within that period. Figure 3.3 shows the

pseudocode for the method invoked for periodic broadcast of Info messages

at a vehicle i. In this method, vehicle i first checks whether it has reached the

zone boundary, in which case it invokes INITIALIZE otherwise it re-invokes

BROADCAST-INFO after (1

f) seconds. Figure 3.4 shows the pseudocode

for RECEIVE-REPLY the method invoked on receiving a Reply message

at a vehicle i. In this method, vehicle i first checks if it lies on the same

side of the Reply message’s sender and Query message’s sender, in which

case it cancels its scheduled broadcast of a Reply message. Figure 3.5 shows

the method invoked on the receipt of an Info message. In this method, the

enclosed warning information is extracted and is delivered to the respective

application.

A vehicle i at position Pi generates the warning information and invokes

the INITIALIZE method. The mode of i changes to Relay and a Query mes-

sage is broadcast. Note that road segments between Pi and boundaries of i’s

transmission range R, form two zones. Any vehicle j at position Pj receiv-

19


Receive-Query(i, Query)1 j ←Query.Sender ID2 Pj ←Query.Sender Position

3 d̂j ←Query.Sender Direction

4 if (d̂j = d̂i)5 then6 s← |Pj − Pi|7 else8 s← R− |Pj − Pi|9 RECXY ← Pi

10 ts ←Time remaining(s)

11 twait = Max(N

ts, T )

12 Sleep(twait)13 if (ReceivedReply)14 then ReceivedReply ← False15 else Mode← Forward16 Broadcast Reply message

17 Sleep(1

f)

18 Broadcast-Info(i, Info)

Figure 3.2: Method invoked at vehicle i on receipt of a Query message

Broadcast-Info(i, Info)1 if (Now < Info.Time Limit and Pi < Info.Effect Area)2 then Broadcast Info message3 if (|Pi −RECXY | = s)4 then Initialize(i)

5 Sleep(1

f)

6 Broadcast-Info(i, Info)

Figure 3.3: Method invoked at vehicle i for broadcast of an Info message

20


Receive-Reply(i)1 j ←Reply.Sender ID2 k ←Query.Sender ID3 if (Pi ≤ PkandPj ≤ Pk)‖(Pi ≥ PkandPj ≥ Pk))4 then Mode← Receive5 ReceivedReply ← True

Figure 3.4: Method invoked at vehicle i on receipt of a Reply message

Receive-Info(i, Info)1 Content← Info.Warning information2 Deliver Content to relevant application

Figure 3.5: Method invoked at vehicle i on receipt of an Info message

ing the Query message invokes the RECEIVE-QUERY method. Distance

s is computed as the distance between Pj and the closest zone boundary

in the direction of motion d̂j of j. The position Pj is recorded in RECXY .

Time remaining() is used to compute the time (ts) vehicle j will take to

travel distance s. Wait time twait is calculated as the maximum ofN

tsand T ,

where N is a suitable normalizing factor.

After the expiration of the wait period twait vehicle j broadcasts a Re-

ply message. However, if a Reply message was received during the wait

period, method RECEIVE-REPLY would have been invoked. The flag

ReceivedReply would be set to true in this method, and on expiration of twait

vehicle j can use this flag to cancel its scheduled Reply message broadcast.

Otherwise, vehicle i changes mode to Forward and invokes BROADCAST-

INFO. In BROADCAST-INFO vehicle j broadcasts the periodic Info mes-

sage if the effect area and effect time are valid. After traveling a distance

s from position RECXY vehicle j is at the zone boundary and the method

INITIALIZE is invoked.

21


i

j

k

Transmission Range of i

l

Zone I Zone IIA B C

sk

sj

Figure 3.6: Sample scenario with vehicle i as initiating vehicle. Blocks depictthe vehicles and arrowheads denote their direction(North/South) of move-ment. vehicle i (solid block) initiates the dissemination.

3.4 An Example

We now present an example of the working of the proposed algorithm for the

scenario shown in Figure 3.6. Before start of the dissemination all vehicles i,

j, and k are in the Receive mode. Vehicle i on reaching point B on the road

detects a hazard, changes its mode to Relay and starts the warning message

dissemination. Vehicle i broadcasts a Query message, with sender ID as i,

sender direction as +X, sender location as B and other fields (as shown in

Table 1) accordingly. The region of i’s transmission range is divided into two

zones - I and II, as shown. Vehicles j, which belongs to zone I, receives the

Query and computes its distance sj as the distance to the zone boundary B.

22


Likewise, vehicle k computes its distance sk, as distance to the zone boundary

A. Similarly, respective ts (time to traverse distance s) values are computed,

and using this each vehicle computes its respective twait ∝ 1ts

, normalized

to lie within [0, T ]. Each vehicle waits for twait time before sending a reply

message, if it has not received one during the wait period. Note that a similar

process shall take place in Zone-II.

As sj << sk, we can assume that vehicle k waits less and sends a Reply

message, in which case it becomes the next forwarder and changes its mode

to Forward. Both vehicles j and i, on receiving the Reply message, check if

it was broadcast from the same zone to which they belong, and change back

to Receive mode. Now, as vehicle k had the least wait time, this implies

it is expected to take the most time to reach the zone boundary of Zone-I

towards which it is headed. Any broadcast of Info message by vehicle k is

guaranteed to reach any vehicle in Zone-I, and vehicle l entering the zone at

a later instant of time, shall be informed by such a periodic broadcast of Info

message by vehicle k.

Note that point A is the last point in Zone-I such that a broadcast by

vehicle k from that point is guaranteed to reach all nodes in Zone-I. Hence,

on reaching point A, vehicle k changes its mode to Relay and broadcasts a

Query message, to handover the task of being the zone-forwarder to another

vehicle, which is currently in zone-I, and is most likely to spend the most

amount of time in this zone.

3.5 Overcoming Network Congestion

In a traffic scenario with a large number of vehicles, which is a characteristic

of heavy or bumper-to-bumper traffic, the delivery of a Query message may

not be guaranteed. This can also be attributed to the fact that message

drop can occur if the periodic Info messages sent by the forwarder in the

adjoining zone collide with the Query message. If the Query message sent

by a forwarder vehicle which is leaving a zone fails to be delivered then the

23


warning information is no longer retained in that zone. In this section, we

propose an extension of the algorithm proposed in section 3.3 which counters

this problem caused by congestion in the wireless network, and can lead to

a misalignment in the protocol.

We propose to counter this problem by suggesting a variant of the algo-

rithm in which all the vehicles in the receiver mode anticipate the receipt of

a Query message in advance. Hence, even if the Query message fails to be

delivered to them, they can emulate the receipt of a Query and broadcast

a Reply message as in the previous case. The periodic Info message sent

to the receiver vehicles by the forwarder delivers the warning information,

but it also encloses the sender’s position. Based on this position the receiver

vehicles can estimate as to when the forwarder vehicle will reach the zone

boundary and broadcast the Query message. Hence, if the Query message

is not received within a timeout period from the expected instant, the re-

ceiver vehicles emulate the receipt of the Query message and broadcast Reply

messages so as to elect the new forwarder for the zone.

Receive-Info(i, Info)1 k ←Info.Sender ID2 Pk ←Info.Sender Position3 d̂k =Info.Sender Direction4 s′ =Compute Distance Remaining(Pk, d̂k, Pj, d̂j)5 if s′ ≤ s′TH

6 then Execute REINITIATE-ELECTION(i,k) after Time remaining(s′) + tTH sec7 Content← Info.Warning information8 Deliver Content to relevant application

Figure 3.7: Method invoked at vehicle i on receipt of an Info message

On receipt of the Info message the receiver vehicles obtain the sender’s

position and direction, and by using that along with the query sender’s po-

sition and direction they are able to obtain the distance s′ which the for-

warder will travel before reaching the zone boundary. Now, if s′ is less than

a threshold distance(s′TH), then the receiver vehicles schedule the execution of

RECEIVE-QUERY at an instant after tTH seconds, at which the forwarder

24


Reinitiate-election(i, k)1 if ReceivedReply == False2 then {}3 else RECEIVE-QUERY(k,Query)

Figure 3.8: Method invoked at vehicle i on non receipt of a Query messagedue to message drop

is supposed to reach the boundary. If the Query sent by the forwarder is

actually received then the scheduled execution of RECEIVE-QUERY does

not take place. Figures 3.5 and 3.5 show in detail the steps of this variant of

the algorithm. Apart from these, all other steps of the algorithm remain the

same shown earlier in Figures 3.1 - 3.4.

25

Chapter 4

Experimental Study

4.1 Simulation Setup

The network simulator employed in the experiments is NS-version 2.28 [15],

and VANET Mobisim-version 1.1 [16] is used as the traffic simulator to sim-

ulate the dynamic traffic scenario and mobility patterns of the vehicles. The

movement pattern of the vehicles, generated by the traffic simulator, in terms

of the current position, speed, and direction, is fed into the network simula-

tor to simulate the associated dynamic network topology over the VANET

at real time. This process is automated by means of a data-pipe between

the two simulators and a server-client, two-way communication takes place

between the traffic and network simulators which synchronize the flow of

data amongst themselves and run in parallel at run time. The detailed spec-

ification and implementation of this integrated simulator can be found in

[14].

The network simulator effectively simulates the characteristic mobility

pattern of moving traffic by periodically seeking position and velocity data

of each vehicle from the traffic simulator. The value of this periodic time

step, VMStime−interval, is kept appropriately small so as to effectively report

movement and changes in the movement pattern of a vehicle to the network

simulator without substantial delay, and is commensurate with the granular-

26

Chapter 4. Experimental Study

Channel : WirelessPropagation : Two Ray GroundMac : Mac/802 11Queue : Drop Tail / Priority QueueAntenna : Omni Antenna (Ht. 1.5m)Transmission Power : 0.2818dBm (250m)Frequency : 914 Hz

Table 4.1: Network parameters

ity of the latter. All vehicles in a scenario being studied are associated with

a single “mobile node group” and hence the update process of their position

and velocity for all vehicles is done concurrently with little time-lag. Hence,

the time granularity of the simulation is indeed VMStime−interval.

The network parameters are summarized in Table 4.1. The time interval

at which the updated position and velocities of the vehicles are read by the

network simulator, VMStime−interval, is set to 1 second, and all other algo-

rithms’ parameters are varied, measured and studied in its respect. Hence,

the absolute values of the parameters bear little significant and all analysis

and performance evaluation of the algorithm is conducted by varying param-

eters in multiples of VMStime−interval. This also contributes to the fact that

the results are independent of the absolute values of parameters. A change

in the value of VMStime−interval would just indicate a changed granularity

of the observed mobility pattern of the vehicles, as perceived by the net-

work simulator followed by an associated increase in the number of periodic

messages and other network-related events occurring in the VANET.

In what follows, we shall refer to the algorithm proposed in Chapter 3 as

the Zone Based Forwarding (ZBF) Algorithm.

27


4.2 Performance Evaluation

Irrespective of the information dissemination protocol in use, the dissemi-

nation process is initialized from one single vehicle which then coordinates

with other vehicles in its range to propagate the warning information. In

order to measure the performance of an information dissemination protocol,

we primarily employ the following two metrics:

1. Coverage: The total number of vehicles in the scenario which receive

the information after the dissemination is initiated. This is a measure

of the effectiveness of the information dissemination protocol in use.

2. Message broadcasts: The total number of message broadcasts that

took place to propagate the warning information. This is a measure

of the overhead incurred by the information dissemination protocol in

use.

However, some dissemination protocols deliver the information to the vehicles

when they are physically present within the perimeter of a demarcated road

stretch (zone/grid). In this case, the distance a vehicle travels before it is

delivered the warning information is employed as a metric to have a further

insight at the performance such a dissemination protocol provides. To be

employed in any VANET application any such information dissemination

protocol should deliver the warning information to an inbound vehicle as

soon as possible.

4.3 Experiments

In this section, we present results of simulations of different dissemination

protocols. We first present a performance comparison of the existing strate-

gies, followed by a comparison of the proposed ZBF algorithm with the rel-

evant existing strategies. Finally, we present results for performance evalua-

tion of the modified ZBF algorithm proposed in Section 3.5.

28


4.3.1 Comparison of Existing Approaches

We conduct the relative performance evaluation of the existing dissemina-

tion strategies, as described in Section 2.1, on a sample highway scenario of

length 2 Km. It consists of one single stretch of road with two lanes per

driving direction and a total number of 200 vehicles. The minimum and the

maximum speed limit for the vehicles are 0 m/sec and 25 m/sec (90 Km/hr)

respectively. The dissemination begins at a randomly chosen instant after

the traffic flow becomes stable. However, this randomly chosen instant is

the same for each dissemination strategy under observation. The periodic

beacons, if employed, are periodic with a period of 1 sec. Figure 4.1and 4.2

10

12

14

16

18

20

22

24

26

28

30

0 0.2 0.4 0.6 0.8 1

Num

ber

of

veh

icle

s in

form

ed (

Cover

age)

q

Torrent-MorenoCongestion Based

Congestion + Delay BasedProbabilistic (p : 1/|SLC|)

Figure 4.1: Comparative performance evaluation of existing strategies :Number of Vehicles Informed (Coverage)

show the coverage induced and message broadcasts incurred by the existing

strategies discussed in Section 2.1, namely, the contention based approach

by Torrent-Moreno and the congestion based approach. In addition, we also

present a variation of the congestion based approach, in which the broad-

29


0

2

4

6

8

10

12

14

16

18

20

22

24

26

28

30

0 0.2 0.4 0.6 0.8 1

Num

ber

of

mes

sages

bro

adca

st

q

Torrent-MorenoCongestion Based

Congestion + Delay BasedProbabilistic(p:1/|SLC|)

Figure 4.2: Comparative performance evaluation of existing strategies :Number of Messages Broadcasts

casting vehicles use a randomly chosen delay period from [0,200 ms] before

broadcasting the message. A vehicle which receives a message within this

delay period does not broadcast the message. Lastly, as discussed in Sec-

tion 2.1.3 we also compare the results of the probabilistic approach, where

the probability that a vehicle re-broadcasts a warning information (p) is in-

versely proportional to its Stabilized Local Congestion.

We observe that both the coverage and number of broadcasts change with

changing q, which is a parameter in the congestion based approach, but re-

main the same for other approaches. The congestion based approach informs

the maximum number of vehicles for q = 0, however the number of broad-

casts is also large. However, the variant of the congestion based approach

incurs far less overhead but reaches almost the same number of vehicles (at

q = 1). Also, the probability based approach has the least coverage. Lastly,

the contention based approach by Torrent-Moreno [2], incurs less number of

message broadcasts but at the same time reaches a greater coverage than any

30


0

20

40

60

80

100

120

140

160

180

200

170 175 180 185 190 195 200

Num

ber

of

veh

icle

s/m

essa

ge

bro

adca

sts

Timescale(in sec)

Number of Vehicles Informed (Coverage)Number of Message Broadcasts

Figure 4.3: Performance of the strategy proposed by Fathy and Khakbaz in[3]. Information spreads to all vehicles as time progresses, starting at t=170

other strategy. Hence, we observe that both the congestion based approach

(with random delay) and the contention based approach perform equally well,

but the performance of the latter is marginally better in some cases. In this

light, the strategy proposed by Fathy et al. in [3] which improves upon the

Torrent-Moreno approach attains greater importance.

Figure 4.3 shows the performance of the strategy proposed by Fathy et al.

in [3]. Since, this approach carries through the dissemination over a period of

time, we see that the number of vehicles receiving the information increases

substantially as time progresses. The number of vehicles informed at the

start of dissemination are better than the Torrent-Moreno approach owing

to the betweenness conditions introduced in this approach. Also, since this

approach is able to deliver the warning information across network partitions

it delivers the warning information to all vehicles in the scenario within a

period of 30sec. The delivery of the warning information to all the vehicles

31


in the scenario is not observed in any of the other existing strategies.

Since, the Torrent-Moreno approach and the approach by Fathy et al. [3]

outperform all existing dissemination strategies, we use them as a reference

for further comparisons in the next section.

4.3.2 Performance Evaluation of ZBF

We now compare the performance of the ZBF algorithm proposed in Chapter

3, and the Stored Geocast algorithm as discussed in Section 2.2. We use

a sample highway scenario of length 10 Km for this evaluation, with two

lanes per driving direction. The total number of vehicles in the scenario

are 500, and the minimum and the maximum speed of the vehicles is 0

and 30 m/sec (108 Km/hr) respectively. We observe the performance of

the two approaches by varying the frequency (f) of the periodic Info and

GATE message respectively. Recall that in the Stored Geocast algorithm

the elected gateway vehicle periodically broadcasts its existence by sending

a GATE(g,loc) message, where g is its grid coordinate and loc is its current

location. The values used for normalizing factor (N) and maximum waiting

time (T ) are 0.1 and 1 sec respectively.

Figure 4.4 shows the coverage achieved by both the algorithms varied with the

frequency (f) of the periodic Info and GATE messages. In case of the Stored

Geocast algorithm, the warning information to be spread is piggybacked upon

the GATE messages broadcast periodically by the gateway vehicle, whereas

in case of the ZBF algorithm, the warning information is contained in all of

the Info, Query, and Reply messages. As discussed in Section 3.1, frequency

(f) of the periodic broadcasts is upper bounded byvmax

Rand is equal to 0.12

(vmax=30 m/sec, R=250 m). The results are sampled at 5 random instances

for a period of 5 minutes for each of the three cases of one, two and three

zones or grids existing in the scenario. Further, the grid length and the zone

length respectively in the two approaches are equal to the transmission range

(R=250 m) of the vehicles. Note that, the results shown in Figure 4.4 are

averaged across all the random instances and all the three cases of one, two

32


0

50

100

150

200

0 0.015 0.03 0.045 0.06 0.075 0.09 0.105 0.12

Num

ber

of

veh

icle

s

Frequency of periodic Info/GATE messages

Number of vehicles moving in/out of a zone

ZBF Algorithm

Contention based

Stored Geocast

Figure 4.4: Total number of vehicles informed v/s Frequency (f) of periodicbroadcast.

and three zones/grids.

We observe that since the information is delivered to only those vehicles

which are present in the zone at any moment of time within the duration of

the experiment, the maximum coverage is bounded by the total number of

vehicles moving in/out of a zone within that period. This also includes the

vehicles which are initially present within a zone at the time of the start of

the dissemination.

The number of vehicles to which the Stored Geocast algorithm delivers

the warning information increases as f increases. However it is surpassed by

the ZBF algorithm when f attains its maximum value of 0.12. At that value

of f the ZBF algorithm ensures that the warning information is delivered

to all the vehicles which are present in the zone at any instant after the

start of dissemination. Note that, the Torrent-Moreno approach delivers the

warning information to a far lesser number of vehicles as it does not retain

the information within the area of interest.

33


0

50

100

150

200

0 0.015 0.03 0.045 0.06 0.075 0.09 0.105 0.12

Num

ber

of

mes

sages

bro

adca

st


ZBF Algorithm

Contention based

Stored Geocast

Figure 4.5: Total number of messages broadcast v/s Frequency (f) of periodicbroadcast.

Likewise, Figure 4.5 shows the total number of message broadcasts by

each of the strategies. As f increases the GATE and Info messages re-

spectively are broadcast more frequently, and hence the number of message

broadcasts increases. We observe that the number of message broadcasts by

the Stored Geocast algorithm far exceeds those by the ZBF algorithm. The

Torrent-Moreno approach incurs less message broadcasts, but it also delivers

the message to less number of vehicles, as was observed in Figure 4.4.

We analyze the different type of message broadcast used by the two strate-

gies in Figure 4.6. We observe that the increased message broadcast in the

Stored Geocast algorithm are due to the large number of BID message broad-

casts employed by it. They are separate messages used by the algorithm for

electing a new leader whenever the previous one exits the grid. Each vehicle

in the grid broadcasts one such message on receiving a RETIRE message

from the outbound leader vehicle. On the other hand, in case of the ZBF

algorithm only one Reply message, in response to a Query message suffices

34


0

20

40

60

80

100

120

140

0 0.015 0.03 0.045 0.06 0.075 0.09 0.105 0.12

Nu

mber

of

mes

sages

bro

adca

st

Frequency of period Info/GATE messages

Proposed Algorithm: Number of Query Messages

Proposed Algorithm: Number of Reply Messages

Proposed Algorithm: Number of Info Messages

GeoGRID Algorithm : Number of RETIRE Messages

GeoGRID Algorithm : Number of BID Messages

GeoGRID Algorithm : Number of GATE Messages

Figure 4.6: Distribution of different types of messages broadcast v/s Fre-quency(f) of periodic broadcast.

to elect the new forwarder for the zone.

Figure 4.7 shows the average distance any vehicle which is inbound to

a zone travels before it is delivered the warning information. In case of

the Stored Geocast algorithm, this is the distance traveled before receiving

the first GATE message broadcast from the leader vehicle. For both these

approaches it is seen that as the frequency (f) of broadcast of Info and

GATE messages respectively is increased, the distance decreases. This is

because with an increased frequency of broadcast, the time period between

successive re-broadcasts decreases and an inbound vehicle is more likely to

receive the information sooner. At lower frequency (f) values the Stored

Geocast algorithm delivers the information within 80 m of the vehicle entering

35


0

10

20

30

40

50

60

70

80

0 0.015 0.03 0.045 0.06 0.075 0.09 0.105 0.12

Dis

tance

tra

vel

led i

nsi

de

a zo

ne

Frequency (f) of periodic Info/GATE messages

ZBF Algorithm

Stored Geocast Algorithm

Figure 4.7: Distance inside a zone which a vehicle traversed before beinginformed v/s Frequency(f) of periodic broadcast.

the grid which is less than the distance in case of the ZBF algorithm. But

as f is increased to the ideal value of (vmax

R) the distance in case of the

ZBF algorithm is observed to be lesser than in case of Stored Geocast by

10 m. Thus, in terms of the distance traveled by a vehicle inside a zone

before getting the warning information for the first time, Stored Geocast

outperforms the proposed strategy at lower frequency (f) values but at higher

values the ZBF algorithm performs better.

We also present a comparison of the performance of the two strategies

under consideration by using the total number of message broadcasts per

informed vehicle as a metric. Figure 4.8 shows the number of messages

broadcast per informed vehicle in case of the Stored Geocast algorithm, the

Torrent-Moreno algorithm and the ZBF algorithm. We observe that the ZBF

algorithm uses far less number of messages per informed vehicle as compared

to the Stored Geocast algorithm. Although, the Torrent-Moreno algorithm

uses lesser number of messages per informed vehicle, but as is evident from

36


0

0.2

0.4

0.6

0.8

1

1.2

0 0.015 0.03 0.045 0.06 0.075 0.09 0.105 0.12

Mes

sage

bro

adca

sts

per

info

rmed

veh

icle


ZBF Algorithm

Torrent-Moreno

Stored Geocast

Figure 4.8: Total number of messages broadcast per informed vehicles v/sFrequency(f) of periodic broadcast.

Figure 4.4, it delivers the information to lesser number of vehicles.

Lastly, we draw a comparison between the ZBF algorithm and the algo-

rithm proposed by Fathy et al. [3] which improves upon the contention based

approach proposed by Torrent-Moreno [2]. Figure 4.9 shows the performance

of the algorithm by Fathy et al. [3] on the same sample highway scenario,

as was used for the other approaches. Since this approach essentially uses

the contention based approach for propagation, we observe that the vehicle

coverage and the number of message broadcasts is similar at the start of dis-

semination (denoted as 0 on the Timeline axis). However, as time progresses

this approach bridges across network fragments and delivers the information

to more number of vehicles and finally to approximately all the vehicles in

the scenario.

Note that this approach delivers the warning information to as many

vehicles as possible and does not take into account whether or not the in-

formation content is relevant for the receiving vehicles. However, if we do

37


0

100

200

300

400

500

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80

Num

ber

of

veh

icle

s/m

essa

ge

bro

adca

sts

Timeline(in seconds, starting from the time of dissemination)

Number of Message BroadcastsNumber of Vehicles Informed

Figure 4.9: Result of the Fathy algorithm [3] on a sample highway scenario.

assume that the information is relevant all the receipts we observe that this

approach takes 20−25 seconds to deliver the information to the same number

of vehicles as in the case of the ZBF algorithm. However, the ZBF algorithm

delivers the warning information, within a distance of 40−80m from the zone

boundary, to only the vehicles for which it is relevant. At an average speed

ofvMAX

2= 15m/sec (vMAX = 30m/sec) this results in a delay of 2.6 − 5.3

seconds. Thus, we observe that the ZBF algorithm delivers the information

to only the vehicles for which it is relevant and in the worst case incurs a

delay of 5.6 seconds for each receiving vehicle, which is lesser than the worst

case delay of 25 seconds incurred by the Fathy et al. algorithm.

4.3.3 Performance Evaluation of ZBF Extension

In this section we evaluate the performance of the extension of the ZBF

algorithm presented in Section 3.5 for overcoming network congestion, if

present in the scenario. In order to observe the effectiveness of this extension

38


0

100

200

300

400

500

600

700

0 0.015 0.03 0.045 0.06 0.075 0.09 0.105 0.12

Num

ber

of

veh

icle

s

Frequency of periodic Info messages

Number of vehicles moving in/out of a zone

ZBF Algorithm

Extended ZBF Algorithm

Figure 4.10: Number of vehicles reached v/s Frequency(f) of periodic broad-cast.

in overcoming congestion, we simulate the protocol over the same highway

scenario but with the number of vehicles increased to 1000. This induces

heavy bumper-to-bumper vehicular traffic and allows us to simulate the drop

of the Query message which is responsible for the handover of the forwarding

task to a new forwarder vehicle in a zone. The values of tTH and s′TH used

for the simulations are 1 sec and 15 m respectively.

Figure 4.10 shows the comparison of the vehicle coverage achieved by the

ZBF algorithm and its proposed extension. We see that in heavy traffic, as

the network becomes more and more congested some Query messages are

dropped however, the proposed extended version overcomes this and still re-

tains the information in a zone by electing a new forwarder. Consequently,

we observe that the proposed extension achieves a greater vehicle coverage

than the standard ZBF algorithm. However, because the receipt of the Query

is emulated by the receiver vehicles in this extension and a subsequent broad-

cast of Reply message occurs, we observe an increased number of message

39


0

20

40

60

80

100

120

0 0.015 0.03 0.045 0.06 0.075 0.09 0.105 0.12

Num

ber

of

mes

sage

bro

adca

sts

Frequency of periodic Info messages

ZBF Algorithm

Extended ZBF Algorithm

Figure 4.11: Total number of messages broadcast v/s Frequency(f) of periodicbroadcast.

broadcasts due to these Reply message broadcasts. In case of a Query mes-

sage being dropped in the standard ZBF algorithm, the receiver vehicles

would not have received the Query message and hence broadcast of Reply

message in response to it would not have had occurred. This is evident from

the result shown in Figure 4.11 which compares the total number of message

broadcasts in the two cases.

Hence, we see that in case of heavy or bumper-to-bumper traffic being

present in the scenario, than the proposed ZBF algorithm extension over-

comes Query message drops and produces a better coverage. But the total

number of message broadcasts incurred are also more as compared to the

standard ZBF algorithm of Section 3.3.

40

Chapter 5

Conclusion

This thesis presented an efficient information dissemination strategy which

incurs small overhead and is capable of retaining the information within

the effect area of the information for the entire duration of its effect time.

The preceding chapters have shown that most of the existing dissemination

strategies do not retain the information within its target area. However,

there exists an algorithm which provides retention of information in the effect

area but incurs a large overhead, making it unsuitable for deployment over

VANETs. In this light, the contribution of this thesis has been twofold:

1. A detailed comparison of the existing information dissemination strate-

gies in VANETs is presented and certain essential characteristics that

an information dissemination strategy must possess are identified. It

is shown that all these characteristics are not present in most of the

existing dissemination protocols.

2. An information dissemination strategy which incurs little overhead is

presented which is capable of retaining the information within the effect

area of the warning information for the entire duration of its effect time.

Further, we demonstrate that how the proposed strategy outperforms

the existing information dissemination protocols in VANETs.

41

Chapter 5. Conclusion

5.1 Future Work

Both safety and convenience applications in VANETs might benefit from

further research on warning information dissemination. Some possible future

work on warning information dissemination in VANETs, with regards to the

ZBF algorithm, can be as follows:

1. Although, the frequency (f) of the periodic broadcasts is empirically

chosen, the exact method to compute it dynamically based on the cur-

rent traffic scenario around a vehicle has been left un-specified. Further

work, may investigate its correlation with other network and mobility

characteristics of the vehicle as well as develop an algorithm to compute

it on the fly maybe devised.

2. The ZBF algorithm aims to build up consecutive zones covering the

entire area of interest of the warning information. However, a zone

with a periodic broadcast frequency f equal to (vMAX

R) guarantees

that any vehicle passing the zone will be delivered the information.

Hence, two such zones which bound the area of interest will in fact

ensure that all inbound traffic is delivered the warning information. A

mechanism which allows these two bounding zones to be set up needs

to be investigated.

3. The zone length, which is assumed here to be equal to the transmission

range (R), can also be setup as a value more than R. We suggest

that such an assumption would also lead to an aspect of probabilistic

delivery of the warning information to the vehicles visiting such a zone.

Note that, in this case the number of forwarders and hence the number

of broadcasts can be further reduced.

4. The periodic Info messages which are of greatest significance for spread-

ing the warning information can also be used as a method of electing a

new forwarder. Any vehicle receiving an Info message which senses its

time remaining to be spent in the zone as more than that of the for-

warder can assume the forwarding role by suitable informing the latter.

42

Chapter 5. Conclusion

However, specific semantics of the changing of the forwarder need to be

determined. Also, the fact that excessive handovers of the forwarding

role might lead to an increase the overhead incurred by the protocol

needs to be investigated.

43

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