Combining the Spray Technique with Routes to Improve the Routing

Process in VANETS

Maur

ıcio Jos

e da Silva

, Fernando Augusto Teixeira

, Saul Delabrida

and Ricardo A. Rabelo Oliveira

1,∗

Department of Computing, Federal University of Ouro Preto, Ouro Preto, Brazil

Department of Computing, Federal University of S

ao Jo

ao Del Rey, Ouro Branco, Brazil

Keywords:

Wireless Networks, Vehicular Networks, Routing Protocols.

Abstract:

Vehicular networks represent a special type of wireless network that has gained the attention of researchers

over the past few years. Routing protocols for this type of network must face several challenges, such as high

mobility, high speeds and frequent network disconnections. This paper proposes a vehicular routing algorithm

called RouteSpray that in addition to using vehicular routes to help make routing decisions, uses controlled

spraying to forward multiple copies of messages, thus ensuring better delivery rates without overloading the

network. The results of experiments performed in this study indicate that the RouteSpray algorithm delivered

13.12% more messages than other algorithms reported in the literature. In addition, the RouteSpray algorithm

kept the buffer occupation 73.11% lower.

1 INTRODUCTION

Vehicular ad hoc networks (VANETs) represent a spe-

cial type of wireless network that has gained the at-

tention of researchers over the past few years. This

type of network offers, through Intelligent Transport

Systems (ITS), such services such as driver assis-

tance, entertainment and dissemination of informa-

tion (Taysi and Yavuz, 2012).

In VANETs, the high mobility of vehicles causes

frequent disconnections among network nodes, which

partitions networks and prevents the use of rout-

ing protocols designed for ad hoc networks. How-

ever, some features of VANETs can be used to as-

sist in routing, such as mobility patterns limited by

roads, the tendency of vehicles to move in groups and

the integration of sensors into vehicles (Toor et al.,

2008) (Li and Wang, 2007). There are several routing

algorithms that have been proposed for VANETs, but

recent technological achievements and their popular-

ization, such as GPS, have opened up the possibility

of proposing even more efﬁcient protocols.

This article introduces the RouteSpray algorithm.

This algorithm combines four important concepts in

∗

The authors would like to thank to Federal University

of Ouro Preto, CAPES, FAPEMIG and SEVA for ﬁnancial

support.

making routing decisions: (i) use of the store-carry-

and-forward technique (Zhao and Cao, 2008) to route

messages; (ii) transmission of messages based on di-

rect contact (Spyropoulos et al., 2008a); (iii) use

of the routes of the vehicles to assist in routing, as-

suming that the vehicles are equipped with GPS; and

(iv) use of the controlled spraying of messages tech-

nique (Spyropoulos et al., 2008b). Keeping in mind

that all the techniques mentioned above are studied in

the literature with the aim of improving the routing

process, the main contributions of RouteSpray are:

• To combine the controlled spray technique using

routes to improve the routing process;

• To explore the geographic routing for mobile des-

tinations;

• To offer a comparative study and a performance

analysis of the controlled spraying technique and

the use of routing information for routing.

Several protocols that aim to perform routing in

VANETs have been presented. The main difference

among these protocols is the information they con-

sider in routing (history of contacts among nodes, lo-

cation information, etc.) and the strategy they use to

forward messages (number of generated replicas for

each message). Nevertheless, there is a consensus

among the scientiﬁc community that there is no ideal

routing protocol that can be applied in all scenarios.

583

José da Silva M., Augusto Teixeira F., Delabrida S. and A. Rabelo Oliveira R..

Combining the Spray Technique with Routes to Improve the Routing Process in VANETS.

DOI: 10.5220/0004871005830590

In Proceedings of the 16th International Conference on Enterprise Information Systems (ICEIS-2014), pages 583-590

ISBN: 978-989-758-028-4

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

The RouteSpray protocol aims to address scenarios

in which the routes of vehicles are previously known,

which has become common due to the popularization

of navigation devices, especially if we consider ﬂeets

with controlled mobility, such as buses, trucks and

taxis. This protocol was designed to use the routes

of vehicles to make routing decisions, which is the

only premise it requires.

The RouteSpray protocol was validated through a

simulation of an urban environment where vehicles

run through routes that connect the points of interest

of a city. To ensure a more realistic simulation, the

OMNeT++ simulator (Varga, 1999) was used together

with the VeNeM software (Silva, 2012). The results

of the experiments show that the RouteSpray algo-

rithm delivered 13.12% more messages than other

proposals reported in the literature and kept the buffer

occupancy 73.11% lower.

The remainder of the paper is organized as fol-

lows: in Section 2, related studies are presented. In

Section 3, the operation of the RouteSpray algorithm

is described. In Section 4, the simulation environment

and the experimental results are presented. Finally,

in Section 5, conclusions and future studies are dis-

cussed.

2 RELATED WORKS

Over the past few years, several algorithms such as the

DSR (Dynamic Source Routing) (Johnson and Maltz,

1996) and the AODV (Ad-hoc On-demand Distance

Vector) (Perkins and Royer, 1999) algorithms have

been proposed to solve the routing problem associ-

ated with ad hoc networks. Both protocols initiate

data transmission only after establishing a path be-

tween source and destination, a characteristic that is

often not satisﬁed in VANETs because this type of

network suffers frequent disconnections caused by the

high speed and high mobility of vehicles. To avoid

data loss, routing protocols for VANETs consider the

use of the store-carry-and-forward technique (Lee and

Gerla, 2010).

Another characteristic that can beneﬁt routing al-

gorithms for VANETs is the use of location informa-

tion of network nodes, which has become possible

due to the incorporation of Navigation Systems (NS)

into vehicles. Routing protocols that use this tech-

nique are classiﬁed as position-based or geographic-

based (Allal and Boudjit, 2012).

Opportunistic transmission and context infor-

mation can both be used in VANETs to improve

the routing process. One of the main algorithms

for vehicle routing is the GeOpps (Leontiadis and

Mascolo, 2007). The GeOpps is a single copy

algorithm, which aims to route data messages to a

speciﬁc geographic region. Its operation is based

on calculating the estimated minimum time to the

message delivery. To achieve this it explores the data

provided by the navigation systems. The calculation

of METD is done as follows: The algorithm traverses

the route of the vehicle looking for the nearest point

to the destination; after the NP is discovered, the

algorithm queries the NS to get the estimated travel

time from your current position to the NP; ﬁnally, the

algorithm adds the time returned by the NS to the

estimated time for the vehicle to travel in a straight

line from the NP to the destination. In general, the

METD can be calculated as follows:

MET D = ETA to NP + ETA f rom NP to D

The GeOpps algorithm was designed for vehicular

networks, and uses the vehicle routes to route mes-

sages toward the destination. However, the fact that

it does not explore alternative paths using multiple

copies of the message causes major delays in the de-

livery of the message, making it unviable for practical

use.

Another scheme that explores opportunistic trans-

mission combined with multiple copies of the mes-

sage to ensure better delivery rates, is called Epidemic

routing (Vahdat et al., 2000). The Epidemic algo-

rithm uses the store-carry-and-forward technique to

improve data delivery rates. It stores received mes-

sages in a buffer and takes advantage of opportunistic

contact to replicate the stored messages to the other

nodes of a network. This technique causes the net-

work to ﬂood with messages and ensures that one of

the replicas of the message follows the shortest ex-

isting path to the destination. Hence, the Epidemic

algorithm achieves a high message delivery rate and

low delay for messages transmitted to the destination.

Nevertheless, due to the excessive number of message

replicas, this type of routing causes network degrada-

tion, abusive consumption of electricity and a large

occupancy of buffers. Such characteristics make the

Epidemic algorithm unusable in various scenarios.

To solve the problems associated with the Epi-

demic algorithm, an algorithm called Spray and Wait

was proposed in (Spyropoulos et al., 2008b). The

Spray and Wait algorithm uses the spray technique to

decrease the number of replicas of messages sprayed

over a network. Although the authors introduced the

use of the algorithm in sparse networks, the spray

technique was ﬁrst used in cellular networks. This

technique aimed to spray messages among the points

that are most frequently visited by users (Tchakountio

and Ramanathan, 2001). The Spray and Wait algo-

ICEIS2014-16thInternationalConferenceonEnterpriseInformationSystems

584

rithm is divided into two phases. In the spray phase,

the source node calculates the number of copies that

must be sprayed. This calculation is based on the

number of network nodes and on the desired de-

lay time for the message to reach the destination.

These copies are sprayed in an opportunistic manner

among the nodes that enter the transmission area of

the source node. If the message is not delivered to the

destination in the spray phase, the nodes initiate the

wait phase. In the wait phase, each node keeps the

message in its buffer until it comes across the destina-

tion node, and only then does it deliver the message.

Although dense networks are beneﬁcial to the op-

eration of the Spray and Wait algorithm, in vehicular

networks, density becomes a trap and compromises

the performance of the algorithm. This negative ef-

fect occurs because the ﬂow of vehicles becomes con-

centrated at intersections and trafﬁc lights then spread

along different directions that vehicles may follow.

Such behavior causes some copies of the message to

be taken away from the destination. As a solution, the

Route Spray algorithm uses the routes of vehicles to

determine the best route through which to send a mes-

sage. The algorithm sprays messages only among the

nodes that will encounter the destination node, thus

preventing the messages from being sprayed among

nodes that can never deliver them.

3 ROUTESPRAY ALGORITHM

To perform routing, the RouteSpray protocol assumes

that vehicles are equipped with GPS and that in addic-

tion to knowing their route, they also know the route

of the message destination. Those are premises of all

position-based algorithms (Mauve et al., 2001). The

RouteSpray algorithm, however, differs from the oth-

ers for predicting the mobility of the destination node.

Furthermore, there is no need for a ﬁxed network in-

frastructure; that is, it is possible to perform the rout-

ing among vehicles in a completely ad hoc manner.

The operation of the protocol is based on the use

of two types of messages: control messages and data

messages. Control messages are used to maintain the

state of a network, which is achieved by sending con-

text information to neighboring nodes. In order to

avoid conﬂicts of messages created at the same time,

each message generated in the network has a unique

identiﬁer, which consists of the address of the source

node, the creation time of the message and a counter.

The process of information exchange and the rout-

ing decision making can be divided into three dis-

tinct stages. In the ﬁrst stage, communication is ini-

tiated by a handshake, when nodes exchange infor-

mation about the packages that have already been de-

livered over the network, allowing for the control of

messages stored in the buffer, which is achieved by

deleting those that have already been delivered. In

the second and third stages, the nodes exchange in-

formation about the state of the buffer. The source

node sends its neighbor a list containing an identi-

ﬁer and the destination of each message in its buffer.

With this information, the neighbor calculates, using

the pre-established routes, the time in seconds that it

will take to deliver each message. After the source

node receives a response from the neighboring node,

it is able to determine which is the best carrier for the

message. More details about the routing stages are

presented below.

Whereas node X entered the broadcast area of the

node Y, the three stages would be as follows:

In the ﬁrst stage, X sends Y a handshake message

that carries the list of messages that had already been

delivered in the network. Upon receiving this infor-

mation, Y is able to go through its buffer deleting the

messages listed as delivered. At the end of this pro-

cess, with a consistent buffer, Y delivers the messages

addressed to X and sends X a list of the messages it

has in its buffer.

In the second stage, when X receives the list of

messages in the buffer of Y, X calculates the time

it needs to deliver each of these messages. Then, it

sends Y a list containing the identiﬁer and the time

required to deliver each message. To calculate the de-

livery time of the message, X travels the destination

route of the message looking for a intersection point

with its route. At the end of this process, if X ﬁnds a

point of intersection, it returns the time in seconds it

takes to go from its current position to that point. If

such intersection point does not exist, the algorithm

returns a negative value, indicating that X is not able

to deliver the message.

Finally, in the third stage, when Y receives infor-

mation about the estimated time that X takes to deliver

each message, it is able to decide which is the best car-

rier for the message. To make this decision, Y needs

to estimate the time it takes to deliver the message it-

self and compare it to the estimated time returned by

X. If Y has more than one copy of the message, it will

use the binary spray technique to spray those copies

to X. If the estimated delivery time returned by X is

shorter than the estimated delivery time returned by Y,

Y forwards the messages to X, making it responsible

for delivering the message to its destination.

The entire routing process described above is pre-

sented in greater detail in pseudo-code:

input: message

CombiningtheSprayTechniquewithRoutestoImprovetheRoutingProcessinVANETS

585

if( received control message ) then

{

if( handshake message ) then

{

Clean Buffer;

Update Delivered Messages List;

Delivers Messages Addressed To Source;

Responds Messages List In Buffer;

}

else

{

if( response to handshake message ) then

{

Receives List Of Messages From Neighbour;

Sends Message Contact Time;

}

else

{

Processes Response Contact Time;

Decides For Better Transmitter;

}

else

{

if( received data message ) then

{

if( message addressed to me ) then

{

Process Message;

}

else

{

Store In Buffer;

}

The improvement in performance afforded by the

RouteSpray algorithm is due to the combination of

two important concepts: (i) use of routes to obtain

prior knowledge of contacts among nodes and (ii) use

of the Binary Spray technique. This combination en-

sures better delivery rates without overloading net-

works. Both concepts are explained in greater detail

below.

3.1 Use of Routes

Geolocation information in a network makes it pos-

sible to have prior knowledge about the position of

the network’s nodes. This feature enables package

forwarding in the direction of the destination and im-

proves data delivery rates. The use of the routes of ve-

hicles ensures that the algorithm can predict the con-

tacts among the network nodes. Thus, the algorithm

can make the best forwarding decision.

Consider three vehicles that follow pre-

established routes (Figure 1), where vehicle B

has a package addressed to vehicle C. Although the

route of vehicles B and C intersect, vehicle B will

choose vehicle A as the best carrier of the message to

the destination because vehicle A will meet vehicle

C before vehicle B does. This process ensures that

the message will be delivered in the shortest time

possible.

Figure 1: Pre-established routes for three vehicles.

3.2 Binary Spray

Routing schemes based on a single copy of a mes-

sage cause major delays in delivery. On the other

hand, routing schemes based on ﬂooding cause net-

work degradation. To obtain the lowest delay in de-

livery without degrading a network, in (Spyropoulos

et al., 2008b), the authors proposed the ”spray“ tech-

nique, which consists in generating a number of con-

trolled copies of messages and spraying them among

the nodes of a network. When a vehicle wants to

transmit a message, it generates a controlled number

of copies (L). To calculate the value of L, the exist-

ing number of nodes in the network and the desired

delay time for the message to reach its destination are

taken into account. Spraying can occur in two differ-

ent ways, which are referred to the authors as Source

Spray and Binary Spray.

In spraying based on Source Spray, the source

node forwards L copies of the message to the ﬁrst dis-

tinct L nodes it ﬁnds. In Binary Spray, the source node

starts with L copies; while node A has n > 1 copies (is

the source or the carrier) and meets another node B

(that does not have any copies), it will deliver to node

B b(n/2)c copies and keep d(n/2)e copies for itself;

ICEIS2014-16thInternationalConferenceonEnterpriseInformationSystems

586

when the node has only one copy, it will choose direct

contact to perform the delivery.

Another feature of the Source Spray technique is

that a message requires only two hops to reach the

destination; that is, the source forwards the message

to the carrier, which becomes responsible for deliver-

ing it to the destination. This feature causes delays in

the delivery of messages in networks with controlled

mobility, which makes such a technique unusable in

VANETs. In Binary Spray, on the other hand, the fact

that the carrier node receives more than one copy of

the message and forwards them in future contacts in-

dicates that this technique performs routing based on

multiple hops, reducing the delivery time of the mes-

sage. Therefore, Binary Spray was chosen as the mes-

sage routing method for the RouteSpray algorithm.

4 PERFORMANCE ANALYSIS

Although the evaluation of routing protocols in real

environments is desirable, the high cost of implemen-

tation and the difﬁculty of mobilizing enough staff

to perform the experiments make such implementa-

tion unfeasible. Consequently, the scientiﬁc commu-

nity evaluates routing protocols through simulations.

RouteSpray performance was evaluated through sim-

ulations, comparing it with the Epidemic, Spray and

Wait and GeOpps protocols, which are the main rout-

ing protocols used for sparse and vehicular networks.

The performance of the RouteSpray protocol was

evaluated according to the following metrics: (i) mes-

sage delivery rate; (ii) occupancy of buffers; (iii)

number of messages sent over a network; and (iv) av-

erage delay of message delivery. The message deliv-

ery rate refers to the number of messages delivered to

the destination and is important in determining the ef-

fectiveness of a protocol. The occupancy of buffers is

deﬁned as the sum of all messages stored in the nodes

of a network. Occupancy must be considered because

devices that are used in mobile networks have restric-

tions regarding storage. The number of messages sent

over a network is the sum of all messages sent, includ-

ing the control messages, and indicates the numbers

of transmissions needed to ensure the delivery of the

messages. The average delay for message delivery is

useful to indicate the efﬁciency of the algorithm to

perform routing.

For the simulation scenario, 16 routes were gener-

ated between the points of interest of Barbacena city,

in Brazil. Because its a city that emerged and de-

veloped without proper planning, its streets and av-

enues arose haphazardly. Thus the graph that repre-

sents such scenario has no standard, unlike the graph

of Manhattan (Bai et al., 2003). For the simulation,

the number of vehicles in the network varied between

5 and 100, generating networks with different densi-

ties. For simulations in which the number of vehicles

is greater than the number of routes, more than one

vehicle travels the same route. In this case, in addi-

tion to the vehicles being distributed evenly among

the routes, the vehicles leave at different times. The

transmission speed was also considered to be higher

than the locomotion speed.

The MiXiM framework (K

opke et al., 2008),

an extension to the OMNeT++ Network Simula-

tor (Varga, 1999), was used for the simulation. Ve-

hicular mobility simulations based on random mobil-

ity models do not correspond to reality because the

movement of vehicles is limited to the restrictions of

streets and avenues (Gamess et al., 2012). Further-

more, parameters such as speed and direction suffer

variations. For this reason, vehicular mobility was

generated using the VeNeM software (Silva, 2012).

The parameters used in the simulation are pre-

sented in Table 1.

Table 1: Parameters used in the simulation.

Parameters Values

Simulation time 2700 seconds

Playground X 1.49 miles

Playground Y 2.51 miles

Amount of nodes 5, 10, 25, 50, 75, 100

L Values 2, 3, 6, 8, 12, 20

Band frequency 2.4 GHz

Transmission power 110.11 mW

Signal attenuation -70 dBm

Package size 512 bits

In the simulation time parameter, the value 2700

seconds was used because it corresponds to the time

required for the vehicle to undertake a circular route,

passing through some points of interest in the city.

For the Playground size parameters, it was used the

values returned by the software VeNeM, that corre-

spond to the size needed to cover all the rotes. The

L Values parameter varies according to the number of

network nodes and respects the minimum limits sug-

gested by (Spyropoulos et al., 2008b). The param-

eters related to the physical environment which are:

frequency band, transmission power, signal attenua-

tion and size of the package, were conﬁgured with

values used by the 802.11b standard. The 802.11b

standard was chosen because the 802.11p, that was

designed to be used in vehicular networks, was dis-

continued (IEEE, 2010).

CombiningtheSprayTechniquewithRoutestoImprovetheRoutingProcessinVANETS

587

4.1 Results

When a scenario imposes no storage constraints, the

Epidemic algorithm delivers all messages that are

sent, which makes it an important tool for comparing

routing algorithms. Another algorithm that achieves

delivery rates similar to those of the Epidemic al-

gorithm and also causes less network degradation is

the Spray and Wait algorithm. Although both algo-

rithms are good sources of reference rather than re-

ferrals., they are designed for sparse networks, and do

not beneﬁt from the characteristics of vehicular net-

works. Therefore, in addition to being compared with

these two algorithms, the RouteSpray is also com-

pared with the GeOpss algorithm, which takes ad-

vantage of the routes of the vehicles to perform mes-

sage routing. Assuming the Epidemic algorithm de-

livers 100% of messages sent over the network, the

RouteSpray, Spray and Wait and GeOpps algorithms

delivered 57.66%, 44.23% and 13.11% of messages,

respectively. The values obtained are presented in

greater detail in Figure 2.

The best message delivery rate is achieved by the

RouteSpray algorithm, as a consequence of the use of

the routes of the vehicles combined with the pulver-

ization of multiple copies of messages. The GeOpps

algorithm had the lowest performance on the num-

ber of messages delivered. This result shows that the

algorithms that use multiple copies of messages out-

performs the algorithms that use routing information.

However, the combination of the two characteristics

has proven more effective than using each one indi-

vidually.

Figure 2: Delivered messages on the network.

As shown in Figure 3, the Epidemic algorithm re-

quires that the nodes have large storage capacities be-

cause each network node stores a copy of each trans-

mitted message. This feature can be perceived more

clearly by observing the transmissions required in a

network with 75 nodes in which, to deliver 15 mes-

sages, the Epidemic algorithm stored 1035 copies of

the messages. The GeOpps algorithm does not make

replicas of the message, therefore its use has no im-

pact in the buffers of the nodes. This characteristic

can be proven by looking at the ﬁgure 3. The Spray

and Wait and the RouteSpray algorithms caused little

buffer occupancy, demonstrating the efﬁciency of the

spray technique, as shown in Figure 4. The Route-

Spray algorithm achieved a buffer occupancy 73.38%

lower than that achieved by the Spray and Wait algo-

rithm because it controls the messages stored in the

buffer, deleting those that have already been deliv-

ered. In the RouteSpray algorithm, the presence of

messages in the buffers of the nodes indicates that the

information that the message was delivered has not

spread enough to reach all the nodes.

Figure 3: Comparison of the buffer occupancy of the three

algorithms.

Figure 4: Improvement in the buffer occupancy by spray

technique.

As previously discussed, the use of control mes-

sages by the RouteSpray algorithm improves data de-

livery rates and controls the buffer occupancy. How-

ever, an additional cost is introduced into the network,

causing a greater number of message transmissions.

This effect is demonstrated in Figure 5. Although the

RouteSpray algorithm results in more message trans-

missions than the Epidemic algorithm, it causes less

overhead in the network because the control messages

have no payload data.

The moment of the message gets its destinantion is

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588

Figure 5: Messages sent over network.

another important feature to be analyzed. Such infor-

mation enable evaluate the efﬁciency of the algorithm

to perform routing. A shown in Figure 6, the algo-

rithm GeOpps has the worst performance, which is

expected because it is an single copy algorithm. The

epidemic algorithm achieves the best result due to a

message ﬂooding algorithm. However, for the net-

work of 10 nodes, caused a bigger delay than other

algorithm due to the number of messages received.

The RouteSpray ensures better results than Spray and

Wait, losing only with sparses networks, of 5 and 10

vehicles. This causes a higher delivery rate and a ma-

jor impact over the average delay time.

Figure 6: Messages sent over network.

5 CONCLUSIONS

Routing in vehicular networks remains an unresolved

problem. Several algorithms continue to emerge for

use under speciﬁc conditions and scenarios. Because

VANETs have several features that are not found in

other types of networks, and such features make it

possible to obtain information that can be used in

routing without incurring an additional cost in a net-

work, the RouteSpray algorithm was proposed in this

study. This algorithm proved to be more efﬁcient than

other algorithms designed for vehicular routing based

on vehicular routes presented to date by the scientiﬁc

community.

Despite the challenge of routing packets through

highly dispersed networks, which is common in

VANETs, the RouteSpray algorithm exhibited a good

message delivery rate, surpassing the performance

of algorithms with previously established efﬁcien-

cies. In addition to a good message delivery rate,

the RouteSpray algorithm also requires little storage

space, which makes it applicable in devices with lim-

ited resources.

The RouteSpray algorithm is suitable for appli-

cation in networks in which the routes of vehicles

are known. One example of a good application of

the algorithm is in transportation companies, such as

bus, taxi or carrier companies. The RouteSpray al-

gorithm offers the possibility of dynamic communi-

cation, even in non-routine situations in which pro-

grammed routing would fail, such as when delays oc-

cur because of changes in trafﬁc or ﬂat tires.

ACKNOWLEDGEMENT

The authors would like to thank to UFOP, CAPES,

FAPEMIG and SEVA for ﬁnancial support.

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