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1. INTRODUCTION

For people living in developed countries the sheer volume of road traffic can be a

daily nuisance. In addition, the road traffic conditions affect the safety of the population

since 1.2 million people worldwide are estimated to be killed each year on the roads1.

For this reason, nowadays the automotive industry and governments invest many

resources to increase road safety and traffic efficiency, as well as to reduce the impact

of transportation on the environment. The application of communications and

information technologies for this purpose has opened a new range of possibilities. One

of the most promising areas of research is the study of the communications among

vehicles and road-side units, or more specifically the Vehicular Ad-hoc Networks

(VANET) [24]. This kind of networks are self-configuring networks composed of a

collection of vehicles and elements of roadside infrastructure connected with each other

without requiring an underlying infrastructure, sending and receiving information and

warnings about the current traffic situation (see Figure 1.1).

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Nowadays, Wi-Fi (IEEE 802.11 based) technologies are the most commonly

used for deploying VANETs. The vehicles are equipped with wireless network

interfaces which use either IEEE 802.11b or IEEE 802.11g standards for access media.

However, these are general purpose standards and they do not fit properly the

requirements of high dynamic networks such as VANETs. Currently, DSRC (Dedicated

Short-Range Communication) [54] has been proposed as the communications standard

specifically for VANETs, it is a short medium range communications service that offers

very low latency and high data rate. DSRC is based upon the standards IEEE 802.11p

and IEEE 1609 family.

Figure 1.1: VANET use case: Warn of obstacle in the road.

The use of IEEE 802.11 (not cellular ) standards implies that vehicles

communicate within a limited range while moving, thus exhibiting a topology that may

change quickly and in unpredictable ways. In such kind of networks, previous to its

deployment, it is crucial to provide the user with an optimal configuration of the

communication protocols in order to increase the effective data packet exchange, as

well as to reduce the transmission time and the network usage (with their implications

on higher bandwidth and lower energy consumption). This is specially true in certain

VANET scenarios in which buildings and distances discontinue communication

channels frequently, and where the available time for connecting to vehicles could be

really short.

The efficient protocol configuration for VANETs without using automatic

intelligent design tools is practically impossible because of the enormous number of

possibilities (NP-problems). It is especially difficult (e.g., for a network designer) when

considering multiple design issues, such as highly dynamic topologies and reduced

coverage. All this motivates the use of meta heuristic techniques [6] which arises as

well-suited tools to solve this kind of problems. Unfortunately, few related approaches

can be found in the specialized literature. In Alba et al. (2006) [2], a specialized

Cellular Multi-Objective Genetic Algorithm (cMOGA) was used for finding an optimal

broadcasting strategy in urban Mobile Ah Hoc Networks (MANETs). Chiang et al.

(2007) [14] developed an Ant Colony based model for resource management in

VANETs. More recently, in Dorronsoro et al. (2008) [17], six versions of GAs

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(panmictic and decentralized) were evaluated and used in the design of ad-hoc injection

networks.

In the present Thesis, we face the Optimal File Transfer protocol Configuration

OFTC) problem in VANETs, which deals with the optimization of VDTP (Vehicular

Data Transport Protocol) [10], by means of five different state-of-the art optimization

techniques (meta heuristic algorithms). This problem lies in the core of any VANET

application, and thus optimal configuration is a major concern. Also, we face many

optimization algorithms because this is a new field, and their relative advantages are

still unclear. These algorithms are two swarm intelligence techniques: Particle Swarm

Optimization (PSO) [31] and Differential Evolution (DE) [61]; two evolutionary

algorithms: Genetic Algorithm (GA) [6] and Evolutionary Strategy (ES) [59]; and a

trajectory search technique, Simulated Annealing (SA) [32]. For our tests, two typical

car-to-car environment instances have been defined: urban and highway scenarios. We

rely on a flexible simulation structure using VanetMobiSim/Ns-2 [3] (realistic VANET

simulator) for optimizing the transmission time, the number of lost packets, and the

amount of data transferred. One additional contribution of this work is to provide the

specialist with a useful platform, embedded within ns-2, to configure network protocols

and hence obtaining a fair QoS control in VANETs.

The remaining of this thesis is organized as follows:

Chapter 2 provides an overview of the field of VANET networks summarizing the

possible applications, applied technologies, and challenges. Also, we introduce the

state of the art in VANETs simulation.

Chapter 3 draws the conclusions and the future work from all the achievements

mentioned in this Thesis.

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2. VANET NETWORKS

The VANET provides an overview about state of the art in Vehicular Ad-hoc

Networks (VANETs) since we have optimized Vehicular Data Transport Protocol

(VDTP) used in this kind of networks. This chapter is organized as follows: First,

Section 2.1 introduces the idea of VANET. Following, Section 2.2 presents the main

characteristics of such networks. In turn, sections 2.3 and 2.4 summarize the main

wireless access technologies and routing protocols used in VANETs. Section 2.5 list a

representative set of proposed applications to exploit, and both, the main research

groups and consortia, that work or have worked designing this kind of networks.

Section 2.6 presents the problem of simulating VANETs and the proposed solutions.

Finally, Section 2.7 provides an outline of challenges and future works that arise in the

networks that are presented in this chapter.

2.1 INTRODUCTION

Equipping vehicles with wireless communication devices is a subject that has

interested the research community and the automotive industry since 80’s [24].

Advances in wireless networking technologies rise to the emergence of Mobile Ad-hoc

Networks (MANETs). A MANET is a self-configuring network composed of a

collection of independent mobile wireless nodes connected with each other without

requiring an underlying infrastructure. Each node in a MANET is free to move

independently in any direction, and therefore change their links frequently. Normally

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the nodes are personal computers or small mobile devices as personal digital assistants

(PDAs), sensors, cell phones, etc. (see Figure 2.1).

Figure 2.1: Example of a MANET network.

The main attraction with the MANET is its immediate and direct application to

the real world, offering the possibility of accessing to a communication network where

for different reasons an infrastructure can not be installed. A very promising and

interesting example of such applications is the use of PDAs and MANET technologies

in emergency and rescue [117, 112], as it can be an area after an earthquake or a major

fire, where the communications infrastructure may have been damaged and unusable.

Soon, the research community and the automotive industry studied the

application of MANET technologies to deploy networks among vehicles equipped with

certain mobile devices as GPS navigators or smart phones. From this work two different

technologies appeared: IVC (Inter-Vehicle Communications) and RVC (Road- Vehicle

Communications). The first one enables vehicles to communicate with each other and it

is also known as communication V2V (Vehicle-to-Vehicle). RVC provides

communications between vehicles and the roadside units (RSU) that gather and

broadcast information, this kind of communication is also known as communication

V2I (Vehicle-to-Infrastructure). The union of IVC and RVC germinated in what we

understand today as Vehicular Ad-hoc Networks or VANETs (see Figure 2.2).

Using this technology vehicles can communicate with each other to transmit

different kinds of information. The interchange of real time traffic information

conditions among vehicles can make driving safer and more efficient, for this reason the

research community is mainly working to develop such applications. For example,

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warning about the existence of an accident is useful for the drivers because they can be

able to reduce the speed and look for alternative routes before reaching the accident

area (see Figure 2.2).

Figure 2.2: Example of a VANET application: Warning of a traffic accident.

The roadside elements such as road traffic signs or traffic lights typically just

provide visual information and usually with an unchanging pattern. However, with the

application of VANET technologies the roadside elements actings as RSU could be

more active in informing users with personalized real-time information. For example, a

dangerous curve sign could warn the driver of a vehicle traveling at excessive speed

before reaching it. Another example would be a men at work signal which may

broadcast information about of the existence of road works, so that drivers would know

their existence in advance (see Figure 2.3).

Figure 2.3: Example of a VANET application: Warning of obstacles in the road.

The term VANET was originally adopted to reflect the ad-hoc nature of these

highly dynamic networks. However, because the term ad-hoc network was associated

widely with unicast routing-related research, there is currently a debate among the

pioneers of this field about redefining the acronym VANET to de-emphasize ad-hoc

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networking [24]. Because this discussion has not yet reached consensus, VANET is the

term used to refer to vehicle-to-vehicle and vehicle-to-roadside communications based

on wireless local area networking technology.

To deploy such kind of vehicular networks we need devices to perform both

transmission and reception of information and to process it, some vehicles to achieve

that include an electronic device called car PC. These devices must be equipped with a

voice recognition system, since drivers can not use their hands to access the typical

human-computer interfaces such as keyboards or touch screens.

2.2 VANET CHARACTERISTICS

VANET networks can be viewed as a subclass of MANETs where nodes are

vehicles or roadside infrastructure elements. However they behave fundamentally

different. The mobility of their nodes is the main and most critical difference. The

mobility of vehicles (nodes) that belong to a VANET is influenced by driver behavior,

constraints on mobility (road restrictions), and high speeds. These characteristics have

important implications for design decisions in these networks.

The major characteristics of VANETs are presented following: Rapid changes in VANETs topology are difficult to manage. Due to high

relative speed between cars network’s topology changes very fast. Different

authors have tried to find solutions to this problem for both highway scenarios

[137, 56] and urban environments [43]. However these results can be applied

only to those specific scenarios and not for both at the same time.

VANET networks are subject to frequent fragmentation, so that messages have

troubles reaching their destination nodes. This issue remains open because, as

the previous problem, the obtained results depend on the treated scenarios. Of

course being connective for VANETs is not important for emergency safety

messages since while the network is not connected there is no problem in safety

point of view.

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Such networks have small effective network diameter. We mainly due to the

speed, the high number of obstacles, and the height of the used antennae. For

this reason links between nodes can be broken frequently.

The devices used to deploy these networks have not significant power

constraints,

unlike sensor and other types of mobile devices used in other kind of

MANETs where limited battery life is a major concern.

The network density is variable because it depends highly on vehicular density.

This may be high in some situations, for example, during rush hours at the

entrance of major cities, or it can be light in low-traffic highway environments.

The topology of the network could be affected by the response of the drivers

after receiving messages. This means that the content of messages can change

the network topology.

2.3 WIRELESS ACCESS TECHNOLOGIES

In this section we present several access standards that could be used for

VANETs connectivity. In general, the aim is to provide a set of air interfaces and

parameters for high speed vehicular communications using one or more available

media. Note that currently the Wi-Fi (IEEE 802.11 based) technologies are the most

commonly used for connecting vehicles by different research groups and consortia

involved in research and development of these networks [115, 133, 41].

Following, we present briefly several connection technologies that have been

considered to be used to deploy vehicular networks. We have defined two different

groups: ad-hoc network (without any infrastructure) and cellular technologies.

2.3.1 AD-HOC NETWORK TECHNOLOGIES

The improvement of ad-hoc connection technologies has boosted the appearance

of VANET networks (see Section 2.1). Currently, it is being discussed the use of

different technologies that do not require any infrastructure for development of

vehicular networks. Below, the most interesting ones are presented.

Wi-Fi (Wireless Fidelity): Generally, Wi-Fi refers to any type of IEEE 802.11 wireless

protocol. More specifically, Wi-Fi is the industry standard for products defined by the

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Wi-Fi Alliance1 and conforming to IEEE 802.11 standard [25]. Wi-Fi standard defines

over-the-air protocols necessary to support networking in a local area and it specifies

physical (PHY) and medium access control (MAC) layers.

There are several specifications in the IEEE 802.11 family which extends the

original one (IEEE 802.11) that supports 1 or 2 Mbps transmission in the 2.4 GHz band.

The most extended ones are the standards IEEE 802.11b and IEEE 802.11g, that

provide 11 Mbps and 54 Mbps transmission in 2.4 GHz band with a maximum range of

500 m, respectively. Most of mobile devices, as PDAs, smart phones or laptops, are

equipped with the necessary hardware to use these two standards. IEEE 802.11a is an

extension to 802.11 that provides up to 54 Mbps in the 5GHz band using OFDM

(Orthogonal Frequency Division Multiplexing) [64] encoding scheme. Transfer rates

increased with IEEE 802.11n standard with a bandwidth up to 500 Mbps. In addition,

there are a number of other 802.11 WG activities that define inter access point protocol

(IEEE 802.11f), MAC enhancements for security (IEEE 802.11i), MAC enhancements

for QoS (IEEE 802.11e), etc.

The main research groups have opted for the use of IEEE 802.11b for its strong

presence in the market. The results, which are being achieved by both simulations and

real tests, are quite encouraging [20].

WiMax (Worldwide Interoperability for Microwave Access): WiMax is

another standard developed by IEEE, the IEEE 802.16 [50]. It was defined as an

alternative to cable and xDSL for providing wireless broadband access over long

distances. This kind of connections operates on licensed or unlicensed spectrum. A

commonly-held misconception is that WiMAX can deliver 70 Mbps over 50 Km.

However, WiMAX can either operate at higher bitrates or over longer distances but not

both: operating at the maximum range of 50 Km increases bit error rate and thus results

in a much lower bitrate. Conversely, reducing the range allows a device to operate at

higher bitrates. In [19], they measured the performance of

different scenarios getting a maximum bandwidth of 20 Mbps and transmissions at a

maximum distance of 6 Km. After publication of IEEE 802.16 standard in 2002, several

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revisions have emerged, in December 2005 appeared IEEE 802.16e specific for mobile

devices.

Bluetooth: Bluetooth technology (IEEE 802.15.1) [5] was originally developed by

mobile phones company Ericsson2 in 1994. It is a short range radio communication

system designed as a wireless alternative to the serial communication RS-232

(Recommended Standard 232) for communication of devices like mobile phones,

PDAs, notebooks, PCs, headsets, etc. It should be cheap and low power consumption

for easy implantation into mobile devices. This is currently the most widespread

communication technology for WPAN (Wireless Personal Area Networks). There are

three different classes of bluetooth according to their coverage and power (see Table

2.1), getting transfer rates up to 3 Mbps and ranges up to 100 meters. These networks

operate on a free frequency band using sufficiently robust security mechanisms.

Class Maximum allowable power Coverag(approximate)

Class1 100 mW (20 dBm) 100 m

Class2 2.4 mW (4 dBm) 10 m

Class3 1 mW (0 dBm) 1 m

Table 2.1: Current bluetooth classes

UWB (Ultra Wide Band): The UWB can be seen as an evolution of the Bluetooth that

comes with the IEEE 802.15.3 standard. UWB is a radio technology that can be used at

very low power levels for short-range (10 m) high-bandwidth (> 500 MHz)

communications by using a large portion of the radio spectrum. It offers transmission

bitrates up to 480 Mbps [15]. One of the most important feature of UWB is the low

power consumption.

ZigBee: ZigBee is based on the IEEE 802.15.4 standard [36] and it is the technology

used in ad-hoc WSN (Wireless Sensor Networks). It presents a fairly limited bandwidth

(250 Kbps) and a coverage up to 75 m. This technology is used mostly in systems

where little information is transferred to very small distances. The greatest quality of

ZigBee is that the power consumption is extremely low.

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DSRC (Dedicated Short Range Communications): DSRC has been proposed as the

communications standard for V2V and V2I communications links (PHY/MAC layers).

More specifically, it is a short medium range communications service that supports

several applications requiring very low latency and high data rate. Nowadays, DSRC

systems in Europe, Japan, and US are not compatible. In the US DSRC will be based

upon the standards IEEE 802.11p and IEEE 1609 family, and will use seven 10 MHz-

wide channels in the 5.85-5.925 GHz bandwidth [54]. IEEE 1609 is a higher layer

standard on which IEEE 802.11p is based.

IEEE 802.11p standard was proposed as a modification of IEEE 802.11a by the

ASTM (American Society for Testing and Materials)3 to better match the vehicular

environment. IEEE 802.11p is an extension to 802.11 in order to add Wireless Accessin

the Vehicular Environment (WAVE). WAVE mode of operation allows data exchange

between vehicular devices in rapidly changing communication environments, where

mobile nodes may move up to 200 Km/h and the distances between them are between

100 and 500 meters. In order to cope with very low latency VANET applications, very

short-duration communications exchanges are required. Regarding the physical layer,

802.11p is very similar to 802.11a, 802.11p is also OFDM-based, with more emphasis

on a reduced channel spacing (10 MHz instead of 20 MHz) to cope with the higher

multi-path effect of urban environments. The data rates ranges are from 3 to 27 Mbps

for each channel, because lower rates are preferred in order to obtain robust

communication. The DSRC spectrum is structured into seven channels (see Figure 2.4).

Channel 178 is the control channel (CCH), which is restricted to safety

communications. The two channels at the ends of the spectrum band are reserved for

special uses. The rest are service channels (SCH) available for both safety and non-

safety usage.

At MAC layer level, DSRC is based on access control provided by the

CSMA/CA (Carrier Sense Multiple Access, Collision Avoidance), but modified to

avoid the hidden terminal problem. In order to achieve that, it implements the message

exchanges RTS/CTS (Request-to-Send/Clear-to-send) [12]. This mechanism avoids

collisions but introduces overload and delay transmissions. For this reason, it does not

implement RTS/CTS in the CCH channel.

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Figure 2.4: DSRC Channel assignment in North America.

Table 2.2 presents the main features of the wireless ad-hoc network technologies presented previously.

Name Coverage Transfer data rates Power consumptionWi-Fi 500m 54 Mbps High

WiMax 5000 m 70 Mbps HighBluetooth 20 m 3 Mbps Medium

UWB 10 m 480 Mbps LowZigBee 75 m 250 Kbps Very lowWAVE 500 m 27 Mbps High

Table 2.2: Features of wireless network technologies proposed to deploy VANETs.

2.3.2 Cellular Technologies

The main drawback of the wireless ad-hoc connection technologies is the link

loss problem when there is not any nearby node, this problem is aggravated when they

are used on nodes with high mobility as in VANETs. In order to avoid this problem

there are different lines of research that do not rule out using cellular connection

technologies such as GPRS, UMTS or HSDPA to deploy VANETs (see Figure 2.5).

Following, we present these technologies:

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Figure 2.5: Accident warning by using GPRS.

GPRS (General Packet Radio Service): GPRS is an extension of Global

System for Mobile Communications (GSM) that offers a packet oriented mobile

data service available to users of 2G cellular communication systems. GPRS

provides data rates between 56 and 114 Kbps. 2G cellular systems combined

with GPRS are often described as 2.5G, that is, a technology between the second

(2G) and third (3G) generations of cellular communication technologies. It is

being used to provide services such as Short Message Service (SMS),

Multimedia Messaging Service (MMS), Wireless Application Protocol (WAP),

Internet access, etc.

UMTS (Universal Mobile Telecommunications System): UMTS is one of the

third-generation (3G) cellular communication technologies, it emerges to offer

the possibility of making video-calls to users of cellular phones. UMTS also

provides Internet access with high quality multimedia content since its data rate

is up to 2 Mbps.

HSDPA (High-Speed Downlink Packet Access): HSDPA is an optimization

of UMTS, hence it is known as 3.5G. The improvements have increased transfer

data rates to 14 Mbps. While real rates remain close to 3 Mbps, which is enough

for one of the most innovative services to emerging technology: access to

television content via the mobile terminal by streaming. Currently, it is being

developing new cellular telecommunications technologies as forth (4G) and fifth

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(5G) generations [49]. However, these two technologies have not yet been

deployed.

2.4 ROUTING PROTOCOLS

Because of the fact that it may be necessary to send a packet through several

vehicles to reach a determinate node a routing protocol is needed. Designing an

efficient and reliable routing strategy is one of the most challenging problem in the field

of VANETs. As these are wireless ad-hoc networks, all nodes behave as routers and

take part in discovery and maintenance of routes to other nodes in the network. An

adaptable routing strategy is required since network conditions change continuously

such as: network topology, traffic density, and network partitioning. Additionally, the

routing protocol may need to provide different levels of QoS to different types of

applications and services. The first solution has been the application of MANET routing

protocols directly or modifying them, however these protocols are unsuitable due to

VANETs and MANETs have critical differences (see Section 2.2). In parallel with this,

some VANET specific protocols are also proposed.

In this section we present different approaches trying to solve the routing

problem in VANETs. But previously, we describe the different communication patterns,

that is, the problem of which nodes will be the receivers of the transmitted information.

This is another problem related to routing strategy.

2.4.1 Communication Patterns

Communication pattern refers to which nodes will receive the packets sent by

the data source. Mainly, we can find two different communication patterns: unicasting

and multicasting. The first one describes communications in which the source node

sends information just to one receiver node (see Figure 2.6.a) and multicasting is the

communication pattern where one node transmits a packet to multiple nodes (see Figure

2.6.b).

The easiest multicasting strategy is to generate a separate copy for each

destination and transmit them separately. However, this is the most costly approach

since it does not use information about the path the packets follow and the routes

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between the source and destinations may follow the same path up to a certain node

(when multi-hop communication is carried out). Although this is a challenging issue,

there are solutions in the literature [16]. There are different multicasting approaches, the

most used ones are: broadcasting, anycasting, and geocasting.

Broadcasting strategies theoretically send information to all nodes in a network

(see Figure 2.6.c), but in practice the information is only received by the nodes on the

broadcasting domain. The anycasting sends a packet to just one destination of a number

potential destination nodes, the node which receives the packet is not specified (see

Figure 2.6.d).

The last multicasting strategy, geocasting, is the most promising approach to be

used over VANET and MANET networks. This strategy sends packets to a group of

receiver nodes that are located within a certain geographic area (see Figure 2.6.e). In

this case there is no definition of any group for a terminal as broadcasting. The

geographical location defines whether a node will receive packets or not.

2.4.2 Routing Protocols Classification

Routing protocols can be classified in two major categories depending on when

and how the routes are discovered, these are: proactive (table-driven) and reactive (on-

demand) protocols. In proactive routing protocols all nodes have consistent and up-to-

date routing information to each node permanently whereas in reactive routing the

routes are created when is needed by the source node.

a) Unicasting b) Multicasting

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d) Broadcasting d) Anycasting

e) Geocasting

Each node maintains one or more tables containing routing information to every

other node in the network when proactive routing protocols are used. When the network

topology changes nodes propagate messages throughout the network in order to

maintain a consistent and up-to-date routing information about the whole network.

These routing protocols differ in the method by which the topology change information

is distributed across the network and the number of necessary routing related tables.

The strategy followed by on-demand routing protocols is different, since the

route is established just when is required for a network connection. When a source node

S needs to connect to a destination node D, S invokes a routing discovery process to

find a route between them. After route establishment, nodes S and D as well as

intermediate nodes store the information regarding the route from S to D in their routing

tables. The route is maintained until the destination is unreachable or the route is no

longer needed.

On the one hand, proactive routing protocols have the advantage of reduced end-

to- end delay, since, upon generation of a network connection request, the route is

already established. However, their disadvantage is the fact that routing information is

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disseminated to all network nodes increasing the traffic and power consumption. Thus,

bandwidth for user traffic is reduced and the operating time of the battery powered

mobile nodes is limited. On the other hand, reactive routing protocols have a lower

power consumption and demand less control signaling. However, end-to-end

connection delay is higher, since upon generation of a connection request between two

nodes, the connection needs to wait some time for the link between the nodes to be

established [46].

Finally, some works have studied the possibility of applying the actual Mobile

IP protocol [109] over vehicular networks [38] and [11]; however this protocol cannot

fulfill the requirements for routing in which not only the hosts but also the backbone is

mobile and multi-hop wireless connections composed of many links with varying QoS

are allowed. Therefore, more adaptive network layer protocols are required. Proactive

or reactive approaches can be followed when designing a routing algorithm for ad-hoc

networks [46].

2.4.3 Routing Protocols for VANETs

There are a high number of routing protocols that can be applied over vehicular

ad-hoc networks in the literature offering different QoS, mostly MANET routing

protocols; therefore this section will give a brief overview of a representation of them.

Some of these protocols are shown in Table 2.3. Following, we present the main

features of the most significant routing protocols.

Protocol Comm. Pattern Scheme Use of geography. Info.

Blinding-Flooding[42]

Broadcasting - No

MPR [58] Broadcasting - No

NES [60] Broadcasting - No

CDS [60] Broadcasting - No

DSR [30] Unicasting Reactive No

AODV [56] Unicasting Reactive No

TORA [53] Unicasting Reactive No

DSDV [55] Unicasting Proactive No

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LAR [34] Unicasting Proactive Yes

FSR [26] Unicasting Proactive No

OLSR [27] Unicasting Proactive No

ZRP [22] Unicasting Hybrid No

MAODV [1] Multicasting Reactive No

GeoTORA [33] Geocasting Reactive Yes

GeoGRID [67] Geocasting Reactive Yes

LBM [35] Geocasting Proactive Yes

GAMER [8] Geocasting Proactive Yes

Table 2.3: Main features of routing protocols applied on VANETs.

Blind-Flooding: Blind-Flooding protocol [42] is the simplest broadcasting protocol.

Each node receiving a packet repeats it by broadcasting (see Figure 2.7) unless a

maximum number of hops for the packet is reached, the packet has been already sent or

the destination of the packet is the node itself. It does not require costly topology

maintenance or complex route discovery algorithms. However, it does not take into

account the available resources at the nodes or links, i.e. resource blindness, and the

nodes receive duplicated packets (see Figure 2.7).

Figure 2.7: Blind-Flooding protocol representation.

Connected Dominating Sets (CDS): CDS [60] establishes a hierarchy within the

network nodes classifying them as dominant or passive. The transmissions of the first

ones should cover the whole network (see Figure 2.8). This algorithm reduces the

network traffic; however, the computation of the minimum connected dominating set

over a given graph is in general an NP-Complete problem [39], thus approximations

must be employed in practice.

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Figure 2.8: CDS protocol representation with dominant nodes in black and passive

nodes in white.

Destination-Sequenced Distance Vector (DSDV): DSDV [55] is a proactive unicast

routing protocol based on the distance-vector. The routing tables are sent after a

significant change in the topology of the network. In DSDV routing tables, each route is

tagged with a sequence number originated by the destination indicating how old the

route is. Each node manages its own sequence number by assigning it two greater than

the old one (call an even sequence number) every time. When a updated route with a

higher sequence number is received, the old route is replaced. In case of different routes

with the same sequence number, the route with better metrics is used.

Dynamic Source Routing (DSR): DSR [30] is a reactive unicast routing protocol. The

main idea is discovering the best cost route for the destination node (discovery

procedure). When a node has a packet to send and it does not know the route for the

destination, it sends out a route request packet (see Figure 2.9.a). While this packet is

being transferred through the network, all the nodes traversed are recorded in the packet

header. A node that knows the route to the destination does not forward the packet

further, but appends the route to the route information already accumulated in the

packet and returns a route reply packet to the source node (see Figure 2.9.b). Using this

information the source node updates its routing cache and delivers the packet to the

destination node through the discovered route. If the discovered route fails, the source

node receives a route error packet and the discovery procedure is invoked again.

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a) Route request packet delivery.

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b) Route reply packet reception.

Figure 2.9: Discovery procedure used by DSR routing protocol.

Ad hoc On-Demand Distance Vector (AODV): AODV [56] is a reactive version of

DSDV protocol. As DSDV, in AODV every node maintains a routing table where there

can be at most one entry for a destination. Each entry has fields like the neighbour node

to relay an incoming packet destined to a specific node and the cost of the selected

route. AODV differs from the distance vector algorithm by its routing table

maintenance mechanism. If there is not an entry for the next hop router destination in

the packet; a new route is discovered by broadcasting a route request (RREQ) packet.

An RREQ packet includes the following fields: source address, request id, destination

address, source sequence number, destination sequence number, and hop count. The

source address is the address of the initiator of the route requesting.

Zone Routing Protocol (ZRP): ZRP [22] was introduced in 1997 as the first hybrid

routing protocol with both a proactive and a reactive routing components. ZRP defines

a zone around each node consisting of its k-neighbourhood called routing zone of node.

This protocol is formed by two sub-protocols, a proactive routing protocol called Intra-

zone Routing Protocol (IARP), which is used inside routing zones, and a reactive

routing protocol known as Inter-zone Routing Protocol (IERP), which is used between

routing zones. A route to a destination within the local zone can be established from the

proactively cached routing table of the source by IARP, therefore, if the source and

destination is in the same zone, the packet can be delivered immediately.

Optimized Link State Routing (OLSR): OLSR [27] is one of the most popular

MANET proactive unicast protocols. It finds an alternative route when a link failure

takes place. Every node broadcasts periodically Hello-messages with information to

specific nodes in the network to exchange neighbourhood information. Sending these

messages the size of the data to exchange to generate routes is lesser since it does not

interchange the routing tables. After receiving this information a node builds an

24

individual routing table. After, the node is able to calculate with shortest path algorithm

the route to every destination node.

Multicast AODV (MAODV): As the name suggests, MAODV is a multicast extension

of AODV. MAODV [1] allows the creation of bidirectional shared trees connecting

multiple source and destination nodes for each multicast group. Multicast routes are

discovered on demand. The multicast route request is broadcasted like the unicast route

request, and the route reply propagates back from the nodes that are members of the

multicast group. However, in MAODV, each multicast group has a leader responsible

for the maintenance storing a sequence number for each group. This number, as in

AODV, indicates the relevance of the route information.

Geocast Adaptive Mesh Environment for Routing (GAMER): GAMER is a

geocasting routing protocol used in several VANET designs. The route to a geocast area

is fragile and can break down at any time. The authors of GAMER [8] propose it to

solve this problem by identifying redundant paths from the source node to the geocast

area. First, the source node sends a JOIN-DEMAND packet using flooding through the

forwarding zone to any node in the geocast area. Once received the packet, the receiver

node responds by sending JOIN-TABLE packet in reverse to the source node. Once the

source node receives this JOIN-TABLE packet is able to start sending the geocast

packets.

2.5 Applications

Previously, we presented the technologies that have been taken into account to deploy

VANETs by the research community and industry.In recent years, an extensive list of

potential applications and services addressed to be applied over such networks have

been proposed. The main factors that have led to this development are:

the progress in the technologies that they need,

the investment by the automotive industry, which sees in this technology a way

to increase both safety and comfort of its products,

and the gamble of governments and institutions because they understand that it

can improve the daily lives of citizens.

25

This is reflected in the large number of projects and consortia that are currently

working on developing VANET networks. Nowadays, the main research foci are in

Europe, USA, and Japan. The following is a non-exhaustive list of some of the

projects/consortia grouped by their geographical areas:

Europe: Prometheus (1986-1994), CHAUFFEUR (1996-2003), FleeNet (2000-

2003), C2C-CC (Car-to-Car Communication Consortium) (2001-currently),

PReVENT (2004-2008), NoW (Network on Wheels) (2004-2008), CARLINK

Consortium4 (2006-2008), and WiSafeCar5 (2009-currently).

USA: PATH (California Parthners for Advanced Transit and Highways) (1986),

IVI (Intelligent Vehicle Initiative) (1998-2004), WAVE (Wireless Access in

Vehicular Environments) (2004), VII (Vehicle Infrastructure Integration (2004-

2006), and VSC (Vehicle Safety Communications Consortium) (2002-2009).

Japan: JSK (Association of Electronic Technology for Automobile and Driving)

(1981), ASV (Advanced Safety Vehicle Program) (1991-2007), and VICS

(Vehicle Information and Communication System Center) (1995-2008).

Additionally, there are some projects which are not specifically proposed to tackle

roblems for vehicular ad-hoc networks as DIRICOM (Diseño Inteligente de Redes

Inalámbricas de Communicación)6 at University of Málaga. However, they address

several design VANET problems offering different results.

Typically, the literature categorize applications in three different groups: safety,

transport efficiency, and information/entertainment applications. Nevertheless, these

groups cannot be seen completely orthogonal. Thus, an application designed to prevent

car crashes improves the efficiency because it avoids the traffic jams that the accidents

may cause. Following, we summarize some existing and potential applications that have

been proposed for VANETs and we present the most important requirements of these

applications.

2.5.1 Safety-related Applications

The applications included in this group are designed to reduce the number of traffic

accidents making trips more safety. Different consortia have designed applications to

achieve this purpose. VSC consortium identified eight potential applications [57]:

26

traffic signal violation warning, curve speed warning, emergency electronic brake light,

pre-crash sensing, cooperative forward collision warning (see Figure 2.10), left turn

assistant, lane-change warning, and stop sign movement assistant.

Figure 2.10: VANET application: Cooperative forward collision warning.

C2C-CC consortium [63] proposed other safety-related applications that could

be used jointly with the ones presented before: approaching motorcycle warning (see

Figure 2.11) or road works warning (see Figure 2.3). Additionally, CARLINK

presented an application of real time weather information and forecast broadcasting.

This application is useful in countries where the weather can change suddenly making

dangerous the road trips, as in Scandinavian countries.

Figure 2.11: VANET application: Approaching motorcycle warning.

Note that these applications require vehicle-to-vehicle (V2V) and vehicle-to-

infrastructure (V2I) communications. The derived technical requirements show the

importance of one-hop broadcast communication (i.e., a vehicle simply transmits a

packet, and every vehicle that is able to receive it directly is considered a one-hop

neighbour), which comes in two flavors: event-driven or periodic [24].

2.5.2 Transportation Efficiency Applications

27

For this second group, the transportation efficiency applications, CARLINK consortium

presented an innovative user guidance approach able to offer optimal routes which may

involve different transportation modes, this approach is called optimal multimodal

transport service [4]. Applying this concept the user is able to take the optimal trip

taken into account that he can walk, drive a car, take the public transport, etc.

C2C-CC [63] analyzed efficient route guidance and navigation applications,

green light optimal speed advisory, and lane merging assistants. But as we have

remarked before, the applications developed to increase safety on our roads also

influence the efficiency.

The requirements of these applications are network technologies to

communicate and the use of a global positioning system as the offered by the American

GPS (Global Positioning System) or the European Galileo. We must emphasize that the

access to low cost GPS receiving devices with Internet connection has also influenced

the growth of this field.

2.5.3 Information and Entertainment Applications

Finally, information and entertainment applications include a set of applications of

different flavors. A representation of this set of applications are: automatic tolling

payment, point of interest notification, fuel consumption management, podcasting

services (see Figure 2.12), and multi-hop wireless Internet access [24]. CARLINK also

proposed applications such as automatic searching of free parking spaces in a given

area, file sharing service, and multiplayer games for the car passengers of different

vehicles via ad-hoc wireless connections.

28

Figure 2.12: VANET application: Publicity board podcasting of a cinema.

These applications have different communication requirements to those

presented previously, since they have less necessity of fault tolerance and response

time. Mainly because the information transmitted is not as critical as in traffic safety

and efficiency applications. Thus, an important consideration for all

information/entertainment applications is whether the application is ideally

implemented using the same communication platform for all application groups or

whether they could be better implemented using competing/separate network

technologies.

2.6 SIMULATION OF VANETs

The emergence of vehicular networks has encouraged the design of a set of new

applications and protocols specifically for these kind of networks. The evaluation of

those in outdoor experiments, by using large-scale networks to obtain significant

results, is extremely difficult due to several issues concerning available resources,

accurate performance analysis, and reproducible results. Indeed, it is neither easy nor

cheap to have a high number of real vehicles and a real scenario for only practical

purposes. It is also difficult to analyze applications and protocols performance in a

inherently distributed and complex environment like VANETs.

Simulation has become an indispensable tool because it makes possible to build

a dedicated VANET for its evaluation. Simulators also gather statistical data about the

network usage during the simulation that allows to measure the protocols performance.

29

Moreover, it is possible to visualize the VANET in order to easily specify the scenarios

for the protocol evaluation.

However, due to the complexity of the real world, a lot of the events related to

the signal propagation that plays an important role in the performance of the outdoor

experiments are missed in the simulations: passing by obstacles, reflection problems,

signal interferences, etc. Thus, simulation also presents an important drawback: the

fidelity of the generated results.

2.6.1 VANET Simulation Alternatives

Nowadays, we identify different approaches trying to solve the complex

problem of VANET simulation. First, the most widely used, the desingner could use a

traffic simulator for generating realistic vehicular mobility traces that will be used as the

input for a mobile ad-hoc network simulator. Second, the designer could use a

specially-designed VANET simulator tool. Finally, some MANET application

programming frameworks allows the developer to test the applications via simulations.

The first approach used for simulating VANETs lies in using road traffic

simulators capable of generating mobility traces, which are later evaluated by an

existing specific MANET simulator. The public availability of many of these MANET

simulators is the main motivation for the success of this approach. However, it has a

major drawback: the majority of VANET applications implies that vehicles react to the

network events and this behavior is difficult to be modelled with this scheme. The most

research community adopt Ns-2 (network simulator) [47] for MANET simulating, even

there are more network simulators as OMNet [51], Ns-3 [48] or OPNET [52].

The number of road traffic simulators which generate Ns-2 format traces is

large: the most comprehensive ones are VanetMobiSim and SUMO, however we can

also find Videlio, RoadSim, CARISMA, VISSIM, and MMTS. There are also traffic

simulators that generate traces for other MANET simulators as CORSIM/TSIS, SJ04,

SSM/TSM, and STRAW. Finally, TraNS and MOVE are simulators which combine the

SUMO mobility model generator and Ns-2 simulator in a unique tool [3].

30

The specially-designed VANET simulators join scalable vehicular mobility

descriptions and network stack modelling in a single tool. These combined approaches

have the big advantage of allowing a direct interaction between the communication

network system and the vehicular traffic dynamics, thus, the first can influence the

second. However, they also have a major drawback: the level of detail of both modules

is necessarily lower than that provided by ad-hoc simulation tools. GGCDCI06,

MoVES, and the GrooveNet are specific VANET simulators [3].

Finally, there are some frameworks as JANE [21], a Java-based middleware

platform for MANET applications programming. It allows the developer to test the

applications in a simulation environment and, also, over real mobile devices.

2.6.2 VanetMobiSim/Ns-2 Simulator

In [3], the authors present a simulator tool based on the combination of the road

traffic simulator VanetMobiSim and the network (MANET) simulator Ns-2 [47],

VanetMobiSim/Ns-2 (see Figure 2.13). This simulator tool is used in different projects

as CARLINK and DIRICOM.

VanetMobiSim is an extension to CanuMobiSim [9], a generic user mobility

simulator. CanuMobiSim provides an efficient and easily extensible mobility

architecture, but due to its general purpose, it suffers from a reduced level of detail in

specific scenarios. VanetMobiSim is therefore aimed at extending the vehicular

mobility support of CanuMobiSim to a higher degree of realism. The main features of

this simulator are that it is specific for VANETs and an open source platform; it

supports both macro-mobility and micro-mobility specification; and it uses intuitive

XML code to specify the different scenarios. However the most important feature of

VanetMobiSim is that it has been validated in actual communication scenarios [23]. Its

main drawback is that it offers a poor documentation.

Ns-2 is an open source network simulator, so it is freely available and the user is

able to modify the source code (C++ and OTcl) [62]. It provides a packet level

simulation over a lot of protocols, supporting several transport protocols, several forms

of multicast, wired networking, several ad-hoc routing protocols and propagation

31

models, data broadcasting, satellite, etc. It incorporates different network flow

generators as web, telnet, CBR (constant bit rate generator), etc. for usingthem in the

simulations. In addition, Ns-2 has the possibility of using mobile nodes. The mobility of

these nodes may be specified either directly in the simulation file or by using a mobility

trace file. In this case, the trace file is generated by Vanet- MobiSim. Finally, other

important feature is that it incorporates several add-ons as the visualization tools NAM

[45] (Network Animator) and TraceGraph [28].

Figure 2.13: VanetMobiSim/Ns-2 basic architecture.

2.7 Research Challenges in VANETs

Advances in wireless ad-hoc communication technologies have made possible the

emergence of VANETs, however the involved research community and industry still

have to address several problems to offer a complete VANET development ready to be

deployed. This section covers current research challenges grouping them in different

topics.

Wireless access technology: Nowadays there are several wireless access

technologies that could be used to deploy VANETs (see Section 2.3). In general,

the research community is working on the specification of a set of air interface

protocols and the parameters for high-speed nodes (vehicles) communication

using available media. Most efforts are focusing on two different technologies:

IEEE 802.11 based (see Section 2.3.1) and cellular (see Section 2.3.2)

technologies.

Spectrum issues: The use of IEEE 802.11 based technologies for VANET

communications needs to allocate these communications at the free spectrum. In

the US the FCC has already allocated 75 MHz of spectrum at 5.9 GHz (from

32

5.850 to 5.950 GHz) for V2V and V2I communications [66]. However, in

Europe there are not a continuos free spectrum band of 75 MHz in DSRC.

Hence Car-2-Car consortium has proposed a derivative of the US approach,

allocating 2 _ 10 MHz for primary use of safety critical applications at 5.9 GHz

[54].

Routing strategies: The performance of MANET routing protocols have

improved quite a lot during the last years appearing several specialized

approaches (see Section 2.4.3). Unfortunately, in case of vehicular networks

certain characteristics make most of these protocols unsuitable (see Section 2.2).

The research community is currently working on three different approaches:

– Opportunistic forwarding [37]: The data is stored until there is an

opportunity to forward it.

– Trajectory forwarding [29]: The road side infrastructure serve as an

overlay directed graph.

– Geographical forwarding [65]: The packets are forwarding towards the

destination based on node geographical location.

These three approaches may be used mixing them developing hybrid solutions.

Message dissemination: VANET applications require broadcast information

continuously (see Section 2.5), thus finding an optimal broadcasting technique is

critical in this kind of networks. Nowadays, several broadcasting approaches are

taken into account,e.g., location-aware broadcasting [41], which limits the

broadcast range only to the area of interest reducing overhead (avoiding the

broadcast storm problem), or clustering [18] where neighbor nodes form clusters

limiting the broadcasting range.

Security and privacy: The potential of the proposed applications for such

networks and the information they may manage could cause some malicious

entity make use of them. Different kind of threats could exist, like fake

messages broadcasting which could cause disruption of traffic or even danger.

Thus, security is an issue that needs to be carefully addressed in the design of

VANETs. Privacy and anonymity must be preserved avoiding identification or

vehicle tracking for non-trusted parties.

33

VANET simulation: Testing the impact of VANET applications before their

deployment is an important issue. Nowadays, simulation seems to be the most

feasible solution for this purpose, however it requires the modeling of driver

behavior in different context, such as an accident [24], apart from wireless

adhoc communication as close as possible to the real world. This is not trivial

and is still an open problem.

Additionally, we have to take into account some socio-economic challenges [24]

since the market introduction of VANET technologies suffers the network effect. That

is, the added value for one customer depends on the number of customers in total who

have equipped their vehicle with VANET technology. Therefore the main question is

how to convince early-adopters to buy VANET equipment. There are several options

that are being discussed like the enforcement by law or the attractive deployment

applications. Also this problem is still open.

As it can be seen from the presented list of challenges, the study of vehicular ad-hoc

networks is an open problem that involves different areas of knowledge. It involves

communication technologies, metaheuristics for optimization problems, cryptography

and intrusion detection for security [7], sociological studies and mathematical modeling

of driver behavior [40], and so on.

3. Conclusions and Future Work

This chapter describes the conclusions drawn from the study carried out in this

Master Thesis and suggests some guidelines for the future work.

3.1 Conclusions

The deployment of vehicular networks is a field with about ten years of intense

research activity and progress. Nowadays, the widely adopted approach is equipping

vehicles with WLAN devices (IEEE 802.11 family). If vehicles can directly

communicate with each other and with roadside infrastructure, an entirely new

paradigm for traffic safety and transport efficiency can be created.

34

In such networks, vehicles communicate within a limited range. In turn,

VANETs are composed with high mobility nodes. Thus, they exhibit a topology that

may change quickly and in unpredictable ways complicating the communication tasks.

Therefore, it is crucial to provide user with an efficient configuration of the

communication protocols in order to offer the best quality of service (QoS) possible

previously to its deployment.

In this Master Thesis we have optimized the VDTP protocol used in peer-to-

peer information transfer in VANETs. In order to do this we have defined the

optimization OFTC (Optimal File Transfer Protocol Configuration) problem, which lies

in searching efficient parameters setting of VDTP protocol that maximizes the amount

of data being transferred and minimizes the transmission time as the number of lost

packets.

The proposed problem has been solved by employing five metaheuristic

algorithms (SA, GA, ES, PSO, and DE) that use the VanetMobiSim/Ns-2 vehicular

network simulator to evaluate the solutions generated during the execution. We have

developed the VDTP protocol in order to simulate it on ns-2. In addition, we have

modified ns-2 simulator adding the functionality of interacting with these metaheuristic

algorithms. In turn, we have defined two different scenarios on which we have solved

the problem (urban and highway instances) based on two real areas of Málaga city.

Finally, we have compared the performance of the obtained configurations with the

defined ones by human experts of CARLINK consortium.

In order to compare the algorithms with each other we have used a

nonparametric test, the Friedman test. The results reveal that PSO performs statistically

better than the others in the urban scenario. Moreover, this algorithm obtains similar

results that the best algorithms (GA and SA) in the highway scenario. The genetic

algorithm also gets quite competitive results for both scenarios.

From the point of view of its real world utilization, PSO returned configuration

can reduce 19.6% of the transmission time in urban scenario and 25.43% in highway

35

areas with regards to human experts configuration, while transmitting the same amount

of data (1,024 Kbytes).

The highest effective data rates is obtained by using the same configuration

(PSO), it is 2402,32 Kbps (300,39 Kbytes/s) and 332 Kbps (41,5 Kbytes/s) in urban and

highway scenarios, respectively. Besides, all the metaheuristic algorithms have obtained

higher bandwidth than that offered by CARLINK experts, except in one case (ES in

highway instance.) Furthermore, all analyzed VDTP configurations have transferred

correctly 1,024 Kbyte files with a non-significant packet loss.

The execution time spent on solving the OFTC problem by the algorithms are

between 80 and 150 minutes for the urban case and between 23 and 60 minutes in the

highway. Although involving a large computational effort is acceptable for designers of

VANETs.

The analysis of the results and the required computational effort lead us to

advise the final use of our automatic design algorithm for this kind of problems.

3.2 Future Work

The research area of vehicular networks is in full swing because of the possible real

applications it offers that could change the lives of users of roadways. In turn, it faces

several challenges that are not easy to solve: the search for wireless technology that best

fits to this type of networks, the selection of network protocols and their configurations

to obtain the best performance possible, and the realistic simulation of vehicles and

their communications, among others.

This Master Thesis work is the starting point of several research lines, the most

notable ones are the following ones:

The use of larger and more realistic VANET scenarios for evaluating in a more

realistic way the fitness function. Additionally, studying how the network sizes

affect the performance of these optimization techniques.

Optimizing other protocols used in VANETs (such as DSR, UDP, ...) through

the use of the strategy used in the Master Thesis, i.e., coupling metaheuristic

techniques and a realistic VANET simulator.

36

Applying on real-world tests the results obtained in this work using real cars

moving through roads, in order to compare the performance against the

simulation results.

Defining these problems as dynamic optimization problems (on-line), since the

problems encountered in vehicular networks depend on the scenario and the

moment they arise. In turn, these problems may be defined in a multi-objective

way.

Besides the future challenges presented above, the field of vehicular networks opens

up a large universe difficult to explore. However, the benefits of reaching the goal

motivate us to invest in this difficult adventure.

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