vehicular density-dependent data
TRANSCRIPT
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VD4: Vehicular Density-dependent Data
Delivery Model in Vehicular Ad hoc Networks
Avijit Gupta1, Vineet Chaudhary2, Vivek Kumar 3, Bharat Nishad4, Shashikala Tapaswi5
ABV-Indian Institute of Information Technology & Management Gwalior, [email protected], 2
[email protected], [email protected], [email protected], [email protected]
Abstract — In this paper, we present the VD4 model for effective
delivery of data packets in vehicular ad hoc networks. The
major challenges in such networks are disconnections, high
mobility and resource poor environment. For providing data
delivery under such constraints we adopt the method of carry
and forward in which a vehicle transfers its data to another
vehicle if it is moving towards the destination. For optimizingperformance in such situations, we can make a probabilistic
estimation as to which path the packet should follow when there
are multiple options available. One such estimation can be
based on road density and the average packet delay on the
selected road. The paper focuses on the development of such a
model that can act as a solution to reduce the packet delivery
delay and improve the data delivery ratio.
Keywords-Vehicular Ad hoc Networks; Road Side Unit; routing
protocol; carry and forward; vehicular density
I. I NTRODUCTION
A Vehicular Ad hoc Network (VANET) is a
communication technology that creates network between
vehicles [1] or roadside gateways to allow information
exchange between users. The importance of vehicular ad
hoc networks is increasing day by day and it is estimated
that they will play a key role in providing transportation in
the near future. Its major application lies in providing safety,
comfort, and critical information to drivers on road. Due to
the increasing concern in this field, many research works are
targeted towards more and more optimization in this area.
Vehicular Ad hoc Networks are useful in scenarios where
a driver wants information, even when he is miles from thedestination. As an example, if he wants to view the traffic
pattern of roads to his destination so as to choose the path
with minimum congestion, he can request for the same even
when he is far from the destination. In such applications, the
user can tolerate some delay. Such a service is difficult to be
provided if the cost is high or the infrastructure is damaged.
VANETs differ considerably from Mobile Ad hoc Networks
(MANETs) because the nodes in VANETs are much faster,
have different mobility patterns and are generally confined
to road maps, which make location estimation much easier
as compared to MANETs. Therefore, the protocols suitable
for MANETs may not necessarily be suited for VANETs
and can be optimized to provide better results. The network
connection in VANETs is generally achieved by Road SideUnits (RSUs) that can either act as router for vehicles to
access the network or just as buffer points(or data island)
between vehicles [11]. While the first option is costly, the
second option is prone to excessive delay as the destination
vehicle might never pass the RSU. In such a situation,
communication between RSUs can be accomplished to
provide connectivity to the destination vehicle, which is
again, expensive. In a resource poor environment, the
vehicles cannot always rely upon RSUs especially if they
are placed very far away. For removing the reliability of
vehicular data transfer on RSUs, we can use the carry and
forward [12] method in which a packet between RSUs can be carried by vehicles themselves. A similar approach was
followed in [13], where data is poured by a data center
along the nodes and they are delivered not only to the
vehicles on these nodes but also to the vehicles on the
intersecting nodes when they move across the intersection.
This type of broadcast is expensive and data is transmitted
to nodes which might not be on the path of the destination at
all.
II. STATE OF THE ART
Many researches have been done on vehicle
communication. Some papers have discussed on mobilitymodeling and optimization of (MAC) issues have been
deliberated upon [4][5]. Many researchers have focused
upon development and routing protocols [6][7].
Transportation safety has been discussed in [8][9] where
inter vehicle communication is achieved with static network
nodes. For comfort and entertainment, real time video
streaming between vehicles has been studied in reference
[10].
2010 Sixth Advanced International Conference on Telecommunications
978-0-7695-4021-4/10 $26.00 © 2010 IEEE
DOI 10.1109/AICT.2010.80
285
2010 Sixth Advanced International Conference on Telecommunications
978-0-7695-4021-4/10 $26.00 © 2010 IEEE
DOI 10.1109/AICT.2010.80
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Multi hop data delivery in VANETs is challenging
primarily because of high mobility and sparse situations that
might be prevalent in areas where the service is required. As
the number of nodes on any road might vary from time to
time, it is extremely difficult to find end to end connectivity
for sparsely connected network. In such situations the
moving vehicles might be used as data carriers.
Furthermore, the data packets may be transferred from
vehicle to vehicle whenever a vehicle moving towards the
destination reaches in the vicinity of a vehicle which was
originally carrying the packet. Thus, through relays and
carry and forward, the packet can be transferred even when
no end to end connectivity is present between the source and
destination.
This paper deals with effective data delivery in
VANETs. We suggest a model to effectively route the
request for the service to the destination and receive the
reply within a tolerable delay time. Any packet might becarried by vehicles to the destination via multiple paths. But
for effective and efficient data delivery, we need to consider
the path in which the data transmission delay is tolerable.
Therefore, at every intersection, the data packet can be
transferred to the RSU present there which can be
transferred to a vehicle which moves along the optimal road
chosen according to maximum vehicular densities and
minimum delay.
The rest of this paper is organized as follows. Section III
describes the assumptions that need to be made to represent
the VD4 model. Section IV describes how to model data
delivery delay based on the VD4 model. Section Vdescribes the VD4 algorithm for vehicular ad hoc networks.
The evaluation of the model is done in Section VI; Section
VII concludes the paper.
III. ASSUMPTIONS
This section states the various assumptions that need to
be made to adequately represent the VD4 model. We
assume that for being a part of the VANET, the vehicles are
sufficiently equipped with wireless transmitters which can
transmit in a short range (100 m-200 m) for transmitting
data packet whenever a vehicle reaches the vicinity of theoriginal data packet carrying vehicle or to the RSU. Every
roadside intersection is equipped with a RSU, which is
capable of storing data packets sent by vehicles as and when
required. The information necessary for the proper routing is
included by the source in the packet at the time of
transmission. Each vehicle and RSU knows its present
location using GPS. This is already available in advanced
vehicles. Vehicles and RSUs also contain the information
about paths that might be statically stored as scaled maps.
The RSU maintains the information of vehicles such as the
speed, direction etc. that passed it and also an estimate of
total number of vehicles present on each path at a given
point in time. This information is periodically updated so
that the evaluation of the optimal path may be done with the
latest information. The vehicles are assumed to move with
uniform speed on a path.
IV. THE VD4 MODEL
The Vehicular Density-dependent Data Delivery Model is
based upon routing data packets based on the calculation of
the successor path which is the path of minimum delay from
the set of paths present on the intersection. For any path to
achieve minimum delay, it must be such that the vehicles
can (i) maximize wireless transmissions so that the time
spent by the packet carried by the vehicle is minimized (ii)
the average speed of vehicle movement on the path (the
average of speed of all the vehicles on the path) must be
high so as to reduce the packet delay.
At any time, any path at an intersection can be divided
into two parts. In the first part, the transmission of data
packets can be done wirelessly and hence quickly and the
other in which the vehicle has to carry the data packet itself.
Since it is difficult to predict the configuration of VANET
after a period of time, therefore that path which gives the
largest distance that can accomplished via wireless
transmission from the source RSU will be the best present
path for transmission because it will be a path of minimumdelay. Consider two RSUs at i and j. Suppose k is a point in
between i and j from where the vehicle has to carry the
packet manually as there are no vehicles in front of it to
transfer the packet to. The basic equation for calculating the
delay for each path at an intersection between two RSUs, i
and j can be written as:
(1)
where:α = Fraction of the path length where data packet can be
transmitted via wireless transmission ( )
β = Wireless Transmission delay per unit distance
lij = The length of the path between the RSUs at i and j
vij = The average speed vehicles on the path from RSUs at i
and j
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δ = Constant used for adjusting delay in case wireless
transmission takes place.
ρij = Vehicular density at the path between the RSUs at i
and j
The above equation is similar to the delay equation
obtained for the VADD Model [6], difference being that in
the aforementioned model, the data transmitted between two
intersection points is either completely wirelessly or
completely carried by vehicles. This might not be true when
intersection points are far from each other or the vehicles
are distributed irregularly in the path. Therefore the path is
divided into two parts, the first being the part where data
can be transmitted wirelessly and quickly. The fraction of
such path is represented by α. In the remaining fraction (1-
α) of the path, the vehicle must carry the packet.
Representing delay in this manner leads to more accuracy.
This can be effectively depicted by Figure 1.
Figure 1 – Depiction of how packet is carried partially by avehicle and partially wirelessly transmitted
After the RSU at the intersection knows the delays of
every individual path, it has to choose which path it should
use to forward the packet. The application of Dijkstra’s
Algorithm is not feasible since information at each RSU is
dynamic. The most optimal path at a particular time might
not remain the same for a long duration of time. Therefore,
computation of the complete path is not feasible.
As a solution to this problem we use the stochastic model
of VADD Model [6]. The expected delay according to the
VADD model for the packet from intersection point Im to In
can be written as:
(2)
where,
Di: The expected packet delivery delay from Ii to the
destination if the packet carrier at Ii uses road rij to
deliver the packet.
Pij: The probability that the packet is forwarded through
road rij at Ii.
N(j): The set of neighboring intersections of Ij
V. THE VD4 ALGORITHM
In this section, we introduce the VD4 algorithm for
optimal routing of the data packets to the destination.
Each time a vehicle passes a RSU, the following
information is provided to it: (i) The time of arrival of the
vehicle (as a timestamp) (ii) The speed of the vehicle (iii)
The direction of movement (iv) Data packets (in case it
carries them). The data packets that are received carry a
unique sequence number which is checked for duplicity at
the RSU. If the packet is already present at the RSU, it is
dropped otherwise it is forwarded to the farthest in range
vehicle on the most optimal path as has been calculated by
the delay model. Consider a situation in which a packet is
carried by a vehicle from RSUi through the most optimal
path to RSUj. The transmission of packet by RSUi
continues till an acknowledgement is received or the
timeout is reached. Once the forwarded packet reaches
RSUj at the other intersection point, the acknowledgement
packet is sent using VANET itself to RSUi, which stops
transmitting packets from then on and deletes it from its
memory. Duplicated packets are ignored by RSUj using the
sequence number of the received packet. Following this
approach, the packet is transmitted till the destination nodeis reached. The basic algorithm can be summarized as
follows:
Notations:
Ii : The Intersection under consideration.
Ri : The transmission range of roadside unit(RSU) at Ii.
Vi : The vehicle under consideration.
Pi : The packet carried by Vi.
Di : The direction towards which vehicle Vi is heading.
Dj : The destination direction of packet Pi.
Vj : The vehicle farthest in direction Dj such that its
distance from RSU at Ii <= Ri.
N[] : The outgoing roads at Ii.
Description:
1. For each vehicle Vi that reaches RSUi, do :
2. if vehicle entry already exists then
update speed, direction and timestamp for Vi.
else
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make new entry for speed, direction and time of
arrival for Vi.
end if
3. If Vi is carrying any packet, Pi then
If Pi is a packet with ACK mark, then
delete Pi from memory of RSU at Ii.
else if Di is equal to Dj then
Transmit Pi from RSUi back to Vi.
Mark Pi as SENT.
else
Vj = SELECT(Dj , Ri).
►Select Vehicle to carry the packet
Give Pi to Vj
Mark Pi as SENT.
end if
end if
4. Leave the intersection Ii.
►Procedure to select the vehicle which will further carry
the data packet.
Procedure SELECT( Di , Ri)
1. j := 0, D = INF, p := 0
2. while j <= n(N) do
dij =
calculate
if D >= Dij then
D = Dij p = j
end if
3. Select farthest vehicle on Road N(p) whose
distance from Ii <= Ri.
4. return the selected vehicle.
The basic approach of the algorithm is to develop a data
delivery model such that packets can be delivered from
source to the destination using the intermediate RSUs. Once
a car reaches a RSU, the packets it carries is checked. If the
packet is an acknowledgement packet, then the packet is
deleted from the memory of RSU. In case it is not present in
the memory of RSU, it is incorporated in the memory and
transmitted to the farthest vehicle travelling towards the
destination. The optimal successor path is selected using the
delay equations stated above. The packets are delivered to
all vehicles moving towards the destination on the same
path until one of the packets is delivered to the RSU at next
hop. When this happens, an acknowledgement packet is sent
from that RSU to the source RSU via vehicle travelling in
that direction. Once the acknowledgement packet reaches
the source RSU, the packet transmission stops and packet is
deleted from the memory of RSU. This continues till the
packet is received by the destination.
VI. PERFORMANCE EVALUATION
In this section, we evaluate the performance of the VD4
protocol. We compare the performance of VD4 with several
protocols like Dynamic Source Routing (DSR)[15], the
epidemic routing protocol [16] , Greedy Perimeter Stateless
Routing (GPSR) [16] and Hybrid – Vehicle Assisted Data
Delivery (H-VADD) [6]. We use the simulationenvironment provided by NCTUns 6.0, which is widely
used to simulate VANETs. The following are the
parameters used during the simulation:
Simulation Area 10000m X 8000m
No of vehicles 180
Number of Intersections 5-50
CBR rate .1 – 1 packet per second
Vehicle Velocity 40km/hr - 60 km/hr
Communication Range 200m
Data packet size 1 KB
A snapshot of a limited section of the simulation area is
shown in Figure 2.
ITS Cars are randomly placed on the paths to depict an
environment. The vehicles move in simulation
environments with a speed of 40km/hr – 60km/hr, which
may vary according to restrictions on a particular path.
Various simulation environments are generated with varying
number of intersection points to effectively simulate packet
Figure 2 – A snapshot of a partial area of the simulationenvironment provided by NCTUns
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delays with the number of intersection points. Also for a
fixed number of intersection points, the distances between
the source and destination are varied to get various delays
associated with various distances. To evaluate the
performance on different data transmission density, we vary
the data sending rate (CBR rate) from 0.1 to 1 packet per
second. The performance of the protocols is measured by
the packet delivery delay and data delivery ratio.
A. Packet Delivery Delay
In this section, we compare the data delivery delay for
moving vehicles to fixed sites using VD-4 and H-VADD.
In the first simulation, the packet delivery delay is plotted
against the Euclidian distance between the source and
destination keeping the number of intersections constant.
The plot is shown in the Figure 3.
As can be very easily inferred, the packet delivery delay
increases with the increasing Euclidian distance between
source and destination. This is because once the Euclidian
distance is increased, the paths leading to the destination
must be increased in length to connect the source and
destination. Thus, on an average the length of path between
two intersection points increases. Since VADD considersthat the data packet between two intersection points is
transmitted entirely wirelessly or carried by a vehicle, the
result obtained can be further optimized. This is done by the
VD4 model, which considers the delay to be a sum of
wireless transmission delay and carry delay at the same
time.
Next, the packet delivery delay is plotted against the
number of intersection points keeping the Euclidian distance
between the source and destination as same. The results are
summarized in the Figure 4. As is evident, the packet
delivery delay increases with the number of intersection
points because a fixed number of vehicles are divided into a
large number of paths thus reducing the number of vehicles
on each path, which leads to reduced path density. H-VADD
gives more delay than VD4 protocol because the probability
of choosing a non optimal path increases with each
intersection point. Since intersection points become more,
data delivery delay is increased.
B. The Data Delivery Ratio
In this section we discuss the performance of VD4
protocol as compared to DSR, GPSR, Epidemic routing andH-VADD protocol. The graph shown in the Figure 5 depicts
the relationship between the data rate and data delivery ratio
for the above mentioned protocols. This was obtained as a
result of VD4 simulation with 180 nodes.
Figure 3 – Packet delivery delay versus enclidian distance
keeping number of intersection points constant
Figure 4 – Plot of Packet Delivery delay versus
Number of Intersections
Figure 5 – Plot of Data Delivery Ratio versus Data
Rate
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As depicted by the low value of the data delivery delay,
the DSR routing protocol is not suitable for sparsely
connected vehicular networks. GPSR cannot make use of
traffic patterns and the geographical approach used leads to
void areas with a few vehicles passing by. This makes its
delivery ratio poor when the vehicle density is low. With
epidemic routing, when we increase the data rate, the data
delivery ratio goes on decreasing because of the MAC layer
collisions, which increase due to increase in the network
traffic. H-VADD shows a considerably optimal
performance. It reduces geographical forwarding distance
and does not have routing loops. VD4 shows similar
performance to H-VADD. It shows better performance that
H-VADD on lower densities when the roads are not
saturated and the packets need to be transmitted both
wirelessly and carried. Once roads are saturated (at a higher
data rate) almost all transmission is done wirelessly and
delivery ratio increases since packet dropping is reduceddue to carrying of vehicles.
VII. CONCLUSION AND FUTURE WORK
VANETs have been estimated to have tremendous use in
the forthcoming years. The paper discussed the novel VD4
protocol, which adopts the carry and forward technique in
which a vehicle transfers its data to another vehicle if it is
moving towards the destination when it reaches its vicinity.
The VD4 delay model defines the delay associated with a
path as a function of fraction of distance that the packet can
cover when transmitted wirelessly as well as the fraction of
distance in which it has to be carried by the vehicle. Thesimulation was performed in NCTUns 6.0 and the results
obtained thereafter clearly show advantage of the VD4
protocol over other protocols.
As a future work, implementation using real vehicular Ad
hoc network is required to evaluate the protocol in real
world application.
ACKNOWLEGEMENT
Finally, we would like to acknowledge the technical and
financial support provided to by ABV-Indian Institute of
Information Technology and Management Gwalior.
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