Hindawi Publishing Corporation
International Journal of Distributed Sensor Networks
Article ID 325027
Review Article
Routing Protocols for Vehicular Delay Tolerant Networks: A
Survey
Hyunwoo Kang,1 Syed Hassan Ahmed,2 Dongkyun Kim,2 and Yun-Su Chung1
1
2
. Electronics and Telecommunication Research Institute (ETRI), Daegu 711-883, Republic of Korea
School of Computer Science & Engineering, Kyungpook National University, Daegu 702-701, Republic of Korea
Correspondence should be addressed to Dongkyun Kim; dongkyun@knu.ac.kr
Received 7 September 2014; Revised 30 October 2014; Accepted 5 November 2014; Published 26 November 2014
Academic Editor: Álvaro Marco
Copyright © Hyunwoo Kang et al. his is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Recently, the delay tolerant networks (DTN) have been utilized in various operational communication paradigms. his includes
the communication scenarios that are subject to disruption and disconnection as well as the scenarios with high delay and frequent
partitioning, that is, vehicular ad hoc networks (VANETs). Due to the several characteristics match, new research paradigm named
as vehicular delay tolerant networks (VDTNs) is introduced. hrough relays and store-carry-forward mechanisms, messages in
VDTNs can be delivered to the destination without an end-to-end connection for delay-tolerant applications. However, the choice of
routing algorithms in VDTNs is still under study. he main objective of routing protocols in VDTNs is to maximize the probability
of delivery at the destination while minimizing the end-to-end delay. Until now, many routing protocols have been proposed
to meet requirements of varying applications. In this paper, we, therefore, provide a detailed study of recently proposed routing
schemes for VDTNs. We also perform comparative analysis on the basis of unique criterion such as forwarding metrics with
their implementations. In addition, open challenges and future directions are provided to make room of interest for the research
community.
1. Introduction
Over the past few years several vehicular network architectures have been proposed, such as vehicular ad hoc networks
(VANETs), vehicle to vehicle (V2V) architectures, and vehicle to infrastructures (V2I) architectures [1]. VANETs are
temporal networks which are self-organized by vehicles to
route the packets. However, it is not easy to establish endto-end path between source and destination by utilizing only
V2V communication, because the communication range of
vehicle is limited and movement of vehicle is very fast. Even
if the communication between vehicles and infrastructures
can be possible, network partition still exists where there
is no infrastructure. hus, most of the studies assume that
the vehicles are always connected to the networks; thus they
could not overcome the network partition problem [2].
here are various causes of network partition in vehicular
networks. When node density is sparse, the network partition
may occur. he other reason of network partition can be
intensive number of nodes in small area. In addition, due
to the data congestion, the network partition can also occur.
In some cases the high mobility of vehicles can cause the
network partition. Hence the successful establishment of an
end-to-end path between a source and destination node is not
guaranteed in vehicular networks [3].
On other hand, the DTN Research Group (DTNRG) lead
by the Internet Research Task Force (IRTF) proposed an
architecture with communication protocol named as bundle
protocol. In DTNs, a message oriented overlay layer called
bundle layer is added [4]. he bundle layer exists above
the transport (or other) layers of the networks and provides
interconnectivity between layers. Application data units are
transformed by the bundle layer into one or more protocol
data units called bundles, which are forwarded by DTN
nodes according to the bundle protocol. he idea is to bundle
together all the information required for a transaction,
minimizing the number of round-trip exchanges, which is
useful when the round-trip time is very large. To help routing
2
and scheduling decisions, the bundles follow store-carryforward mechanisms. In delay tolerant networks (DTNs), it is
common that there is no end-to-end path between source and
destination. he DTNs are deined as those networks which
embrace the concept of occasionally connected networks that
may sufer from frequent partitions. In a real environment the
vehicles are distributed over a wide area and move randomly,
and the network is easily partitioned. hese characteristics
of vehicular networks are similar to DTNs. Hence, vehicular
networks can be treated as DTNs and deined as vehicular
delay tolerant networks (VDTNs) [5, 6].
Generally, the bundle protocol of DTN does not provide
details of routes for data packets between the nodes. It deals
only with the forwarding phase. Since, enabling end-to-end
connectivity in vehicular networks is a signiicant issue and
needs to be addressed by appropriate routing approaches,
therefore, a number of studies have been carried out for
applicable routing protocols based on diferent schemes, such
as model-based schemes, epidemic schemes, and estimation
schemes [7]. A very simple protocol is direct delivery, in
which the node originating a message carries it until it meets
its inal destination. In irst contact routing, the nodes forward messages to the irst node they encounter, which results
in a random walk search for the destination node. Epidemic
routing [8] replicates messages to all encountered peers that
still do not have them. If message storage space is unlimited
and contacts between nodes are long enough, epidemic
routing minimizes the delivery delay and maximizes the
delivery ratio. However, those resources are usually limited,
epidemic wastes storage and bandwidth in comparison with
other protocols. For instance, surround routing [9] tries to
minimize the storage consumption and overhead by also
sending messages to all the nodes, but only the nodes that
surround the inal recipient will keep the copies longer than
others. Spray-and-wait [10] generates � copies of a message.
In normal mode, a node gives one copy to each contact; in
binary mode, half of the copies are forwarded to a contact.
Once only a single copy is let, it is forwarded only to the
inal recipient. Spray-and-wait is another example of protocol
that limits message replication as compared with epidemic
routing. he PRoPHET (probabilistic routing protocol using
history of encounters and transitivity) [11] protocol transfers
the message to a neighbor if it estimates that the neighbor
has a higher likelihood of being able to deliver the message to
the inal destination based on past node encounter history.
Similarly, MORA (multiobjective robotic assistance) [12]
learns from the structure of the node movement patterns
and uses this information to improve the message routing.
Moreover, to further increase the delivery ratio, MORA
introduces autonomous agents that adapt their movement
based on the variations in network capacity and demand.
Conclusively we can say that some schemes try to choose
paths through denser areas, which may cause congestion.
Others store data in ixed relay nodes until a vehicle going to
an adequate destination passes by, which may take some time.
Additionally more researches try to forward the data along
the direction to the destination, which may also take some
time. Finally, some schemes combine trajectory information
and traic statistics to ind the best path, which may be
International Journal of Distributed Sensor Networks
complex. Table 1 summarizes the properties of the traditional
routing protocols representing VDTNs.
Mostly, the VDTNs are characterized by generally short
contacts between nodes and a highly dynamic network topology, where routing is a particularly a challenging problem
[13]. Mostly routing protocols that need to exchange control
information during contacts to update routing tables or other
information databases have less time to transfer data bundles.
For example, PRoPHET requires some overhead for maintaining the estimates of meeting probabilities. On the other
hand, routing protocols that do not maintain such control
information generally have to create more bundle copies to
achieve the same delivery performance. his represents an
eiciency compromise, as more copies spend more storage
and transmission resources, contributing to congestion. As
the network topology is highly dynamic, nodes have to
take into account that any information maintained may
be outdated soon. Moreover, applying store-carry-forward
approach directly to vehicular networks may cause a lot
of packets replications which may lead to data congestion
especially when vehicles are dense [14]. So, there is also a
compromise between the value of information exchanged
and the cost of keeping it updated. here are other research
challenges related to routing such as the optimal placement
of relay nodes, traic diferentiation, and congestion control
[15]. It is worth mentioning that the performance of most
of the introduced routing protocols highly depends on the
level of cooperation and autonomy of the nodes. By default,
most of the protocols assume full node cooperation and
little attention have been devoted to study the efect of
reduced levels of cooperation. In fact, by applying and inetuning simple knowledge-based cooperation mechanisms,
the routing performance can be considerably improved [16].
In addition, it is not the only purpose of routing protocol
to overcome the network partition problem. here are a
lot of important issues to design routing protocols, such as
data delivery rates, data transfer time between source and
destination, energy eiciency, bandwidth consumption [17].
he application is also important because there is no routing
protocol that can satisfy all these issues. hus most of proposed routing protocols are designed for speciic applications
[18]. However, these protocols are not suitable for applications
having packets with diferent importance and requirements.
In order to deal with this issue, some researchers provided
adaptive routing protocols with diferent metrics [19].
Hence, we conclude that vehicular DTNs have been
investigated for diferent applications with a large number of
proposed routing algorithms.
1.1. Motivation. From the literature, we can easily ind out
some quality survey papers in various areas of VANETs [20].
However, the focus of those surveys is mostly built around
routing issues in VANETs without taking DTN characteristics
into account. Later, some authors in [21] took the initiative
to provide the performance of VDTNs routing protocols.
However, any comparative analysis has not been performed.
Hence, the current literature still lacks in thorough studies
providing more insight on the routing issues in vehicular
International Journal of Distributed Sensor Networks
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Table 1: Summary of VDTN routing protocols.
Scheme name
Number of message copies
Type
Message replication
Target
Direct delivery
Single
Direct
None
First contact
Single
Probabilistic
Low
Epidemic routing
Multiple
Blind looding
High
Surround routing
Multiple
Limited looding
Moderate
Spray-and-wait
PRoPHET
Multiple
Multiple
Controlled looding
Probabilistic
Moderate
Moderate
Node moves and delivers the packet directly
Packet is delivered in result of random walk search
to its destination
Enormous data propagation
Packets only looded to the nodes near to the
destination
Limited copies of packet are generated
Packet forwarded on the basis of encounter history
DTNs. In this paper, we, therefore, provide a comprehensive
review of vehicular delay tolerant networks (VDTNs) routing
protocols. Furthermore, we also perform a comparative
analysis of selected protocols while deining some metrics
such as forwarding metrics, infrastructure-assisted, locationinformation, topology assumptions, implementation, and
main objectives. Moreover, we summarize the future research
directions in this demanding paradigm.
he rest of this paper is organized as follows. In Section 2,
we present the detail of selected DTN routing schemes
proposed for VANETs. Section 3 provides the comparative
analysis of vehicular DTN protocols. Open issues and future
directions are given in Section 4. Finally, Section 5 concludes
this paper.
2. VDTN Routing Protocols
As mentioned before, the routing protocols in VANETs
aim to establish end-to-end connectivity between network
nodes, which is quite diferent from the case of the delay
tolerant environment. hus, routing protocols in VDTNs
use the store-carry-forward paradigm of DTNs to deliver
data. his paradigm is based on the premise that the endto-end network path may exist over time. However, the
bundle protocol, which is the base of DTN, does not
address routing problems without any establishment of routes
between nodes. For that purpose, several projects are working
for VDTN research independently from VANETs and we,
therefore, categorize proposed forwarding mechanisms for
VDTNs as shown in Figure 1. he VDTN stack consists
of looding, random/probabilistic, infrastructure/incentivebased, and information-based forwarding. Due to the
promising and reliable performance of V2I architecture, we
will focus on infrastructure and information-based routing
protocols in the following section.
2.1. MaxProp (Maximum Priority). MaxProp is a routing
protocol designed for vehicular DTNs. he MaxProp protocol
is based on a store-carry-forward mechanism which is usually
utilized in a DTN environment. However, the authors in [22]
proposed an algorithm which enables the nodes to assign the
priority to the packets. On the basis of the given priorities,
each node can decide either to transmit or drop the packet.
In VDTNs, the transmission duration and opportunities for
each node are limited, since the nodes move fast in sparse
VDTN
forwarding
Flooding
Random/
probabilistic
Navigation
- Moving vector
- Geolocation
- Moving direction
Information
based
Infrastructure
based
Incentive
based
Network
resources
Social
network
- Optimization
- Various traic
- Congestion
- Similarity
- Social graph
- Friendship
Figure 1: Classiication in VDTN forwarding.
areas. Moreover, the bufer of node is also limited in a real
environment. herefore, to decide the priority of packets in
a bufer of nodes is important when performing eicient
routing.
In MaxProp, when two nodes communicate, they
exchange packets in a speciic order. If the node currently in
contact is the destination node of some packets, these packets
are transmitted irst. Secondly, the routing information is
exchanged which includes the estimated probability of
meeting any node. he calculation of the probability is based
on the number of encounters between two nodes. In the end,
an acknowledgement of delivered data is transmitted.
In addition, MaxProp also introduced a mechanism to
handle old data within the network. In MaxProp, each packet
stores a hop list of nodes that the packet already traversed.
his hop list enables each node to identify the age of packets.
he packets with lower hop list values are considered new
packets and thus higher priority is assigned to them as shown
in Figure 2. In case of any node encounter, the packets with
the highest priority are transmitted irst and the remaining
packets are transmitted later. On the other hand, the packets
which have the lowest priority (i.e., higher hop list count) will
be deleted irst in case a bufer is full.
2.2. PBRS (Probabilistic Bundle Relaying Scheme). he roadside units (RSUs) support communications between vehicles
4
International Journal of Distributed Sensor Networks
Packets toward the encounter node
High priority:
transmit irst
Routing information based on
historical data
V0
Acknowledgements of delivered data
Vk
Vj
Packets with short hop list
Low priority:
delete irst
Other packets
Figure 2: he priority of packet in MaxProp.
Source RSU
Coverage area
Destination RSU
Uncovered area
Coverage area
Figure 3: VDTN in PBRS.
and infrastructures for numerous applications. However,
in real environments, RSUs cannot cover all the roadside
areas because of the deployment cost. hus, communications
over relaying vehicles are considered one of the solutions
to support the uncovered areas by RSUs. Some typical
researches utilized store-and-forward techniques for relaying
data between RSUs and vehicles. he RSU transmits its data to
the incoming vehicles which enter its transmission range. In
this case, if an RSU transmits its data to all the vehicles which
are passing by it, a lot of replicated packets are generated
in the network. herefore, PBRS [23] proposed a decisionbased scheme which makes RSUs determine whether or not
to release its data to a vehicle on the basis of certain criterion.
Figure 3 shows the vehicular delay tolerant network which is
considered in PBRS. he source RSU � has data to forward to
the destination RSU �. However, there is no end-to-end path
between � and �. he Vehicles passing by � makes � become
aware of the speed of those vehicles. PBSR calculates the
release probability by utilizing the speed of vehicles. When
a vehicle �� enters a communication range of �, the � holds its
data until the vehicle moves out of the range or a next vehicle
��+1 enters the coverage area. If the ��+1 is faster than �� and
��+1 is considered to reach � before the �� does, � transmits
its data to ��+1 .
2.3. ASCF (Adaptive Carry-Store-Forward). ACSF also
assumes that RSUs cannot cover all the roadside areas like
PBRS. ACSF utilized a store-and-forward technique for
relaying data. However, it focused on the outage time of a
target vehicle in an uncovered area. In the ACSF scheme, a
Uncovered area
by RSU
RSU1
RSU2
Figure 4: Communication in ASCF.
message forwarding mechanism was proposed for reducing
the outage time for vehicles [24].
Figure 4 shows the deployment of vehicles and RSUs
considered in ACSF. he authors implemented ACSF for two
RSUs partially deployed and leaving uncovered area between
them. Here, the uncovered area means the road segment
which is not in the transmission range of any RSU(s). In
Figure 4, it is shown that the vehicles move from let to right
side of the road. Ater the entrance of �0 in the covered area
of RSU1 , it starts communicating data with RSU1 . Since �0 is
moving, ater some time it will be entering into the uncovered
area. However, the vehicles �� and �� can still be used as a
relay to receive the remaining data from RSU1 and forward it
to �0 . For this purpose, RSU1 selects the node which provides
longer connectivity to �0 , thus decreasing the outage time.
he outage time can be calculated by the moving speed of
each node. Since RSU can be easily aware of its transmission
range and the moving speed of nodes moving in it, RSU can
calculate when �0 moves out of its communication range.
Before node �0 leaves the coverage area, RSU1 selects the
relay node with a maximum connectivity time with �0 . ACSF
assumes that �0 is required to adjust its speed in an uncovered
area for a longer connection with a relaying vehicle selected
by RSU1 .
2.4. FFRDV (Fastest-Ferry Routing in DTN-Enabled VANET).
FFRDV is a protocol which was proposed for sparse ad hoc
networks to support a highway road environment where vehicles are moving with high speeds and few traic lights [25].
In FFRDV, the roads are divided into logical blocks based
on geographic information. Each vehicle can get its current
location by GPS and it shares its location and speed with
other vehicles in the same block by hello messages. When an
emergent event occurs, FFRDV selects message ferries which
have the responsibility of relaying data according to velocity
based strategy.
First, the vehicle which senses an event becomes an initial
ferry. It selects the fastest vehicle within its block as a next
ferry. Second, if the ferry enters a new block Bi, it broadcasts
a hello message to ind a new ferry. Any nodes, which are
able to receive a new data, send a response message, including
their current speed. he ferry node compares the speeds and
inds the fastest vehicle �� . If �� is faster than it, it sends the
International Journal of Distributed Sensor Networks
5
The motion vector of
vehicle A
Vehicle A
Vehicle B
Vehicle C
Figure 5: Concept of DARCC.
data to �� or it holds the data. his mechanism is performed
repeatedly block by block.
2.5. DARCC (Distance-Aware Routing with Copy Control).
he routing decision aims to determine how to replicate or
forward message copies to the suitable nodes. DARCC applies
this concept of DTN routing to vehicular environments [26].
he vehicles in DARCC determine whether to transmit data
or not to their encountering vehicles with 2 principles. If
the location of the destination of data is available, the data
is forwarded to the vehicle that is closer to the destination.
Otherwise, DARCC prefers spreading the data to diferent
direction to increase the probability to meet destination.
Figure 5 shows the concept of DARCC, where each
vehicle in DARCC is equipped with a GPS, thus the vehicle
can calculate its current motion vector. he motion vector
is the speed of vehicle and its moving direction. he vehicle
� turns let in junction during certain time �, then its
motion vector of time � is calculated like arrow in the
Figure 5. Each vehicle periodically broadcasts a beacon
message including its location, current motion vector, and
the list of the messages it has. If the vehicles are moving
in diferent directions, the replication helps to perform the
successful delivery, because the other vehicles may reach its
destination on its way before the source. hus, the vehicles �
and � replicate their packets to each other, respectively.
2.6. DAWN (Density Adaptive Routing with Node Awareness).
he authors of DAWN in [27] assume an urban sensing
applications. As shown in Figure 5, there are � ixed sensor in
roadside, and one base station for data gathering. he sensors
are regularly deployed and the base station is located at the
center of the network area. he data packets are generated at
the sensors, and each packet includes its origin location and
generation time. he vehicles and mobile nodes are more like
travelling in the random cells. When the vehicles moves into
new cell they collect the data packet from sensors and store it
in its bufer. If two vehicles meet, they replicate their packets
to each other.
he data forward strategy in DAWN is decided by the
density of the cell. If density is low the forward strategy is
the same as epidemic, that is, a node replicates all the data
Sensors
Base station
Mobile nodes
Figure 6: Network model in DAWN.
it has to encounter nodes. On the other hands, if the density
of cell increases, the throughput is restricted by congestion
due to the limitation of wireless channel capacity. herefore,
in DAWN the UIV (utility incremental value) is proposed to
give priorities to the packets. he packets with higher UIVs
should be transmitted with higher priority (Figure 6). he
UIV is estimated by each node to maximize the probability
of packets to be delivered to the base station before deadline.
2.7. GeOpps (Geographical Opportunistic Routing). Geographic routing is one of the most promising approaches
for eicient routing, which takes location information of the
vehicle into account. Geographical opportunistic routing for
vehicular networks (GeOpps) aims to enhance the performance of single-copy routing protocol in VDTNs [28]. It
exploits the geolocation of vehicles to forward the geographical bundle opportunistically towards the inal destination
location. hus, the vehicle that is heading towards or near the
destination location of the bundle becomes the next bundle
carrier. he closest point where a vehicle carries the bundle is
called nearest point and used to compute minimum estimated
time of delivery (METD) as follows:
METD = time to nearest point +
remaining distance
average speed
(1)
A vehicle with the lowest METD is the candidate bundle
forwarder/carrier. GeOpps assumes that the bundle carrier
6
always ind another vehicle when it arrives at the nearest
point. In some cases, it might be practical to handover
bundle(s) to the vehicle moving slowly to a destination rather
than the vehicle that will just reach the nearest point faster.
To achieve this, GeOpps assigns weights according to varying
speed of vehicles and their remaining distances to the nearest
points. However, it does not provide a method to optimally
calculate these weights.
2.8. GeoSpray (Geographical Spray in VDTN). GeoSpray
[29] uses the principles of single-copy single-path GeOpps
to perform multicopy multipath bundle routing approach.
Multicopy routing schemes are noted for their high delivery
ratios, low bundle delivery delays, and high overheads due
to duplicated copies. hus, GeoSpray adopts the replication
approach of the spray-and-wait protocol [7] to limit the
number of copies. Initially, it uses a multiple copy scheme,
which spreads a limited copies of the bundle to exploit diverse
paths. Aterwards, it switches to a single-copy forwarding
scheme. GeoSpray clears the delivered bundles from vehicles’
storage by propagating the delivery information. As a result, it
achieves better delivery ratio than GeOpps at the cost of high
replication overhead. However, this overhead is less than the
epidemic protocol and similar to spray-and-wait.
3. Comparative Analysis
In this section, the comparative analysis of the previously
discussed VDTN routing protocols is presented. We compare
and analyze the above mentioned schemes based on the
following metrics.
International Journal of Distributed Sensor Networks
routing protocols such as [22, 25, 27] are designed to be
well-operated without any support of the infrastructures.
Moreover, some VDTN routing protocols assumed that the
support of infrastructures can be provided in the limited
area. Since the routing performance depends on the existence
of infrastructure, it is an important metric when analyzing
VDTN routing protocols.
3.3. Location Information. In most of the routing protocols,
including VDTN routing protocols, the packet should be
forwarded from the source node to the direction of the destination node. herefore, if the source node can distinguish
whether the encounter node is near to the destination node
or not, it can perform the routing eiciently.
Nowadays, since a lot of vehicles include equipped GPS
devices, the various VDTN routing protocols which use the
GPS-based location information are proposed. However, if
the source node does not know the location of the destination
node, the source node cannot calculate the distance between
an encounter vehicle and the destination node based on the
location information. Hence, some VDTN routing protocols
which does not require GPS location information are proposed [22]. Moreover, in some VDTN routing protocols, not
only the GPS information but also map information are used
to determine optimal next forwarder. herefore, the location
information is considered as a promising metric to classify
VDTN routing protocols.
3.1. Forwarding Metric. Most of VDTN routing protocols
utilize the store-carry-forward mechanism. Hence, these
protocols usually do not make any end-to-end path between
source and destination vehicles. In epidemic routing which
is one of the most famous store-carry-forward routing,
the vehicles replicate all the data they have to all vehicles
they encounter. However, in above mentioned schemes, the
vehicles which have data should determine whether or not
to forward data to encountering nodes with some criteria.
herefore, we deine these criteria as forwarding metrics in
VDTNs. he forwarding metric is one of the most signiicant
features for distinguishing routing protocols.
3.4. Topology Assumptions. In Section 3.2, we also described
that assumption about existences of infrastructures is an
important metric for analyzing VDTN metric. In fact, besides
the existence of infrastructures, various VDTN routing protocols also have their assumptions such as network models,
mobility model, and traic characteristics. In particular,
topology assumptions such as location of encounter vehicles
is one of the most important assumptions since various
routing performances such as routing overhead or coverage
of the proposed schemes highly depend on the assumptions.
In addition, although some VDTN routing protocols can
achieve high performance improvement over the particular
topologies, it cannot achieve the performance improvement
over another topologies. Hence, even though the topology
assumptions are not costly, they are still important metrics
for analyzing the VDTN routing protocols.
3.2. Infrastructure Assisted. As mentioned in Section 1, the
infrastructures such as RSUs have been installed to support
the vehicle-to-vehicle (V2V) communications for increasing reliability, reducing transmission delay, and so forth.
herefore, some VDTN routing protocols assumed that the
infrastructures can support the V2V communication in a
whole roadside area, thus improving routing performances.
However, this assumption is impractical since the installation
of infrastructures costs so much. In the real world, the
infrastructures are installed in limited roadside areas and
they can support the V2V communications within their
coverage (the localization of the RSUs is still a part of research
but out of scope in this paper). herefore, some VDTN
3.5. Implementation. As mentioned in the previous sections,
VDTN routing protocols have own assumptions such as
infrastructure existence, location information, and topology assumptions, and some assumptions are impractical in
real-world. Hence, even if some VDTN routing protocols
can improve routing performance academically, it cannot
achieve the improvement in real-world. Hence, performance
measurement methods of each proposed routing protocol
such as test-bed based measurement, numerical analysis,
and simulation based analysis is one way to verify the
practicality of the proposed VDTN routing protocols. Hence,
we classify the VDTN routing protocols according to the
implementation.
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Table 2: Comparative analysis of VDTN routing schemes.
Scheme
name
MaxProp
[22]
Forwarding metrics
Infrastructure Location
assisted
information
Topology assumption
Implementation
2
30 Buses in 150 miles; 60 days Real environment
of trace
(UMass DieselNet)
20 km one way road vehicle;
Java-based
interarrival time: 5–120
simulator
seconds
Target
Gives priority to
packets in bufer
Hop count historical
data
No
No
Velocity-based
probability
Yes
Yes
Minimum outage
time of node
Yes
Yes
Velocity of node
No
Yes
DARCC
[26]
Location of
destination moving
direction of nodes
Yes
Yes
DAWN
[27]
Density of nodes
No
Yes
GeOpps
[28]
Density of nodes
Yes
Yes
260,000 vehicles 15 km ×
15 km area
OMNet++
Optimize delivery
ratio, delay, and
overhead
GeoSpray
[29]
Density of nodes and
diferent data size
Yes
Yes
100 mobile nodes with an
average speed of 50 km/h city
of Helsinki, time: 6 hrs
VDTNsim
Optimized routing
with minimum delay
PBRS
[23]
ACSF
[24]
FFRDV
[25]
Not available
Numerical analysis
1500 m × 1500 m area; average Network Simulator
speed of node 60 km/h
2
100 vehicles in 3000 m ×
Opportunistic
3000 m area; each road has 4
Network
lanes; average speed of node
Environment
60 km/h
(One) simulator
5000 taxi in Beijing city 30
Simulation with
days of trace 25 × 25
real environment
Manhattan grid
data
3.6. Target. In common VDTN routing protocols, when the
source node meets another node (viz. encounter node), it
should determine whether or not to transmit its packet to
the encounter node. At this point of time, the source node
calculates a “cost” based on forwarding metric which is
described in Section 3.1. he source node transmits its packet
if the cost of encounter node is low. Hence, the forwarding
metric can represent the target of routing protocol, but it is
not at all times. For example, when the source node wants
to transmit its packet to the destination as soon as possible,
the speed of encounter vehicle can be used as the forwarding
metric. In addition, even if the source node wants to maintain
connectivity with the selected encounter vehicle, the speed of
encounter vehicle also can be used as the forwarding metric.
herefore, not only the forwarding metric but also the target
of protocols is an important metric to analyze VDTN routing
protocols.
Table 2 shows the comparative analysis of the VDTN
protocols discussed in this survey. In PBRS, a velocity of
node is utilized to calculate the release probability. If several
nodes are in the communication range of RSU, the node with
higher speed tends to reach destination faster than slower
speed node. For this reason, faster nodes get higher release
probability in PBSR. hus, we call this forwarding metric
velocity-based probability in the table. Similarly, in ACSF
[24], the maximum hop counts are two between the source
and destination. he only RSUs are the only source nodes in
this scheme. Due to the limitation of communication range,
the connectivity between an RSU and a vehicle cannot be
maintained. In order to overcome this problem, a relaying
vehicle is selected. When multiple vehicles are available for
Reduce packet
replication
Maximum
connectivity
Minimize
intermittent nodes
Reduce packet
replication
Optimize channel
usage
relaying, the one which can maximize the connectivity is
selected. he velocity of relaying vehicle and target vehicle is
important factor to keep the connectivity. Unlike PBRS, the
fastest node is not important in ACSF, because it is easy to
maintain the connection if the speeds of the two nodes are
similar.
DARCC [26] and DAWN [27] utilize packet replication
mechanism like epidemic routing. Packet replication is a
useful technique to increase delivery ratio in DTNs, but
it may result in a waste of network resources. hus, to
control the amount of replicated packets appropriately is a
signiicant issue in these protocols. First, DARCC assumes
two situations. If the location of the destination is available,
the data is forwarded to the vehicle that is closer to the
destination. he data is forwarded to the node which is
moving in diferent direction to spread the data over a wide
area with a small number of replicated packets. On the other
hand, DAWN focuses on the density of nodes in the cell. If
the density increases, the congestion also increases. DAWN
reduces packet replication only if the channel is congested. It
tries to maximize the local channel capacity if the throughput
does not fall due to the congestion.
Performance evaluation of the given schemes also varies.
Some of them such as MaxProp and DAWN were tested
in real test bed environments. In MaxProp, the authors
utilized 30 buses to cover a wide area of 150 square miles
in their test bed. Furthermore, the MaxProp had a realistic assumption that the nodes had no network global
information (global information here includes location of
other nodes). In addition, there was a limited infrastructure
support assumed for QoS. Similarly, DAWN consisted of a
8
International Journal of Distributed Sensor Networks
database, based on a real environment for its test bed with
30 days GPS records of 27848 taxis in Beijing city for simulations. However, the remaining schemes were simulated using
the Network Simulator 2 (NS-2). Also, the Opportunistic
Network Environment (ONE) simulator was considered for
the performance evaluation of the VDTNs routing protocols.
CCN concept to vehicular communications (named
as vehicular CCN, that is, VCCN) needs to be investigated. In addition, a number of challenges still require
attention in VCCN, such as naming, name resolution,
routing, content storing, management and policy of
forwarding information base and pending interest
table management, security, and trust issues.
4. Open Issues and Future Directions
In this section, we describe open issues and challenges for
VDTN routing protocols. he need to address the emerging
number of services in the vehicles has given rise to an
increase in research in vehicular communication. he key
challenge is routing due to the dynamic topology changes.
Many protocols have been discussed in the previous sections.
However, there still exist some challenges and open issues that
need to be investigated.
(i) Most of routing protocols assume either the highway scenario or the urban scenarios. he protocol
which is designed for such environments may not
show eicient performance in a more complex environment. For example, the vehicles may enter the
urban area ater passing highway. herefore, variety
environments should be taken into account at the
same time.
(ii) In most studies for VDTNs, the bufer management
of vehicles is overlooked. Only the size of bufer is
described, but how it can be managed is not described.
he bufer management is important in DTN, because
a lot of DTN protocols are based on store-carryforward mechanism. herefore, reallocating bufer
space and maximum use of other resources can also
be addressed.
(iii) Most of the routing protocols utilize the location
information of nodes. he location information
acquisition is not easy when the destination node is
mobile. For the stationary node, every node is aware
of the nodes location. Hence, location information
can be an eicient metric for routing. Another issue
is the implementation of the routing protocols in
the real world scenarios. Better performance can be
predicted from the protocols applied in the real world
scenarios.
(iv) here always exists a tradeof between delivery ratio,
end-to-end delay, and network resource usage while
applying diferent approaches in the vehicular networks. hus, a completely diferent algorithm with
existing methods can be expected to minimize the
tradeof through, for example, artiicial intelligenceaware routing.
(v) In addition, a few researchers have focused on
integrating the new promising paradigm, that is,
information centric networking (ICN) into VANETs
[30]. Recently, content centric networking (CCN) has
been proposed for the future internet. Since CCN is
at its early stage, many issues are still unidentiied
and open. herefore, the feasibility of applying the
(vi) he content routing is one of the actively researched
parts of VCCN [31]. Request and response forwarding between consumer and provider nodes is the
responsibility of the routing scheme. he simplest
routing scheme which has been used in the CCN
is the breads-crumb technique. However, we need
eicient routing schemes to fulill requests efectively
and eiciently for the purpose of achieving QoS in
dynamic topologies such as VANETs.
5. Conclusion
In this paper, we have performed a detailed survey of recent
developments in vehicular DTNs with more emphasis on
routing. To the best of our knowledge, this is the irst work to
present the comparative analysis of selected vehicular DTN
(VDTNs) routing protocols with respect to unique metrics
such as implementation, infrastructure assisted or not, and
more. In addition, we provide a list of open challenges and
future directions. Finally with this paper, we aim to motivate
further research interest for existing routing constraints in
VDTNs.
Conflict of Interests
he authors declare that there is no conlict of interests
regarding publication of this paper.
Acknowledgments
his research was supported by the MSIP (Ministry of
Science, ICT & Future Planning), Korea, under the C-ITRC
(Convergence Information Technology Research Center)
support program (NIPA-2014-H0401-14-1004) supervised by
the NIPA (National IT Industry Promotion Agency). his
research was also supported by the Basic Science Research
Program through the National Research Foundation of Korea
(NRF) funded by the Ministry of Education, Science and
Technology (2012R1A1A4A01009954).
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