Wireless Sensor Network, 2010, 2, 919-923
doi:10.4236/wsn.2010.212110 Published Online December 2010 (http://www.scirp.org/journal/wsn)
A Novel Routing Algorithm for Vehicular Sensor Networks
Mohammad Jalil Piran1, Garimella Rama Murthy 2
1Departement of Computer Science and Engineering, Master by Research Information Technology, Jawaharlal Nehru
Technologic al Uni versi t y , Hyderabad, India
2Communication Research Centre, International Institute of Information Technology, Hyderabad, India
Received October 31, 2010; revised November 1, 2010; accepted November 8, 2010
Abstract
Recent advances in wireless communications are diffusing into many new applications. The tiny sensor node,
which consists of sensing, data processing and communicating components, led to the idea of sensor net-
works. A sensor network composed of a large number of sensor nodes that are densely deployed either inside
the phenomenon or very close to it. The applications envisioned for sensor networks vary from monitoring
inhospitable habitats and disaster areas to operating indoors for intrusion detection and equipment monitor-
ing. In most cases the network designer would have little control over the exact deployment of the network.
Nowadays Vehicular Networks are drawing lots of attention due to the wide variety of applications that they
can provide. These applications include traffic monitoring, positioning, security etc. A lot of research work is
being conducted to define the standard for vehicular communication. These include frequency allocation,
standards for physical and link layers, routing algorithms, security issues and new applications. In this paper
we discuss the disadvantages of the traffic monitoring by traditional methods and by using GPS equipped
sensors. Then we propose a new routing protocol for a fixed topology containing both stationary and mobile
nodes. We also try to optimize the energy of the sensor nodes. We simulate our routing algorithm in MAT-
LAB and evaluate it for different possible cases.
Keywords: Wireless Sensor Networks, Vehicular Sensor Networks, VANETS, Routing,
Global Positioning System (GPS), Network Lifetime
1. Introduction
Recent advancements in electronics and wireless com-
munications enabled the manufacturing of cheap and
small sensor nodes. A Wireless Sensor Network (WSN)
consists of numerous sensor motes which sense the data,
communicate with each other hop by hop and eventually
report the data to the Base Station. Though WSN started
for military applications, gradually it found to have very
useful applications in wide range of areas like Health,
Building Monitoring and Factory Automation etc. [1]
Research in wireless communications is facilitating the
development of Inter-Vehicle Communication systems
that will benefit mobility and safety objectives. For ex-
ample, an alert message about a traffic accident or traffic
jam can be pr opagated tens of mile s along the roa d to help
drivers select a better route. Recently, these systems,
referred as Vehicular Ad-hoc Networks (VANET), are
gaining significant prominence from both government
agencies and private organizations. [2] In the last 15
years Intelligent Transportation Systems (ITS) have
been researche d and deploy ed in t he US, Europe and Asia
to alleviate congestion and enhance the performance of
traffic networks. With the rapid advances in wireless
communication technologies, vehicles in a transportation
network can seamlessly communicate to obtain informa-
tion about network conditions, thereby, assisting better
decision making. [3] The data collected from the sensors
on the vehicles can be displayed to the driver, sent to the
Road Side Units (RSU) or even broadcasted to other ve-
hicles depending on its nature and importance. The RSUs
distribute this data, along with data from road sensors, weather
centres, traffic control centres, etc to the vehicles and also
provides commercial services such as parking space
booking, Internet access and gasoline payment. [4, 5]
VANET (Vehicular Ad Hoc Networks) is a kind of
MANET (Mobile Ad Hoc Networks) with some common
characteristics, such as movement and self-organization
of nodes. However there are some differences in some
ways. MANET can contain many nodes that cannot re-

M. J. PIRAN ET AL. 920
charge their power and have un-controlled moving pat-
terns [6]. Although the power is not a constraint in the
vehi c l es , V AN E T ha s s om e c ha l le n ge s as : 1 ) p re di c t ab le ,
high mobility that can be exploited for system optimi-
zation; 2) dynamic, rapidly changing topology (due to
high mobility); 3) constrained, largely one-dimensional
movement due to static roadway geometry; 4) poten-
tially large-scale; 5) partitioned [7]; 6) Vehicles are not
comp le tel y reli ab le . [8]
2. Related Work
In this section we deal with some of the traffic monitor-
ing techniques right from manual control by traffic po-
licemen to advanced systems which gain use of GPS
Technology.
1) Traffic control by Police Men manually, e.g. there
are some police check posts in distances between cities
where they monitor the traffic flow by human eye or by
using some equipment such as sonars. This method doesn’t
give satisfactory results. Some of the problems associ-
ated with this are as follows:
 It is difficult to monitor traffic along every road .
 Human errors and low accuracy in monitoring can
be considered as major problem.
 They cannot continue this work 24 hours of 7 days
of the week due to bad weather or lack of light, etc.
2) Roadside Cameras and Sensors are used to monitor
traffic, collect data .The data is then sent to the police
station. Though issues with the previous method are re-
solved there are other issues with th is method.
 High cost.
 Low reaction.
 Constant maintenance is required.
 Doesn’t cover the road completely.
 Fault Tolerance.
3) Global Posit i oni n g Sy st em (GPS).
GPS was primarily designed for military applications
only, but after that the US government made it free for
the other applications too. The GPS consists of 24 satel-
lites that were started by Defence Ministry of the USA
(with NavStar as its pseudonym). The first satellite was
sent in 1978 and the others started their work in 1994.
Each satellite can operate only for 10 years and it will
be replaced before its dead time. Satellite's speed is
around 7000 m/h, the weight of each satellite is almost
907 kg and when its wings are open it is around 8.18
meter long. Power consumption by each satellite is
around 50 Watt [9].
The GPS satellites send two short and burst signals as
L1 and L2. The personal GPS devices can receive L1 at
the UHF band with the 1575.42 MHz frequency. These
signals can pass the clouds, gas and plastics, but not the
obstacles as solids, building and mountains.
A GPS signal consists of three data bit:
1) An unreal-random Code: It is simple as an ID code,
which is to identify sender satellite.
2) Temporary Data (for a day): Location of each GPS
satellite at each time can be estimated based on this
kind of data.
3) Annually Data: The most important data that each
satellite sends about its status.
Vehicles gain the advantages of GPS system in two
ways: Offline Mode and On line Mode. In both there is a
device embedded on vehicles which can receive the sat-
ellites signals and estimate the position of the vehicle. In
offline mode there is one MMC Card required for each
vehicle to save data whereas in the online mode a GMS
is used to send data to the station by the SMS format.
The data stored in the MMC Card can be retrieved via
sophisticated software and in onlin e via industrial mobile
hardware the data is readable in the station.
Disadvantages:
a) GPS's signals are under the effect of the following
which attenuate them [10]:
1. Delay of Troposphere (the lowest portion of At-
mosphere) and Ionosphere: Satellites signals become
weak when the pass the atmosphere.
2. Multiple Signals: It occurs when GPS signals before
reaching the receiver reflect by the buildings or rocks.
3. Receiver Periodical Errors: Surely receiver's time is
not working as proper as GPS satellites, therefore it is
prone to high errors about t im e meters.
4. Orbit Error: Temporary data might not report the
exact location of the satellite.
5. Obstacles: Some other satellites, buildings, trains,
electronic obstacles , crowde d trees c an prev ent si gnals.
6. Satellites Geometry: Satellites geometry is pointed to
the proportional location of satellites. When the sate-
llites are on the same way or they are in the small
groups, some geomet ry errors happen.
7. Satellite's signal intentional corruption: This was
made by Defence Organization to prevent using of
robust signals of GPS satellites by unauthorized
people.
b) Hardware constraints:
1. The necessity of additional hardware as GPS receivers,
MMC Card, SIM CARD , ...
2. Less accuracy (up to 15 meters in positioning and
0.5 km/h for velocity).
3. Dependency on GPRS system in online mode.
4. Failure of MMC Card in the offline mode.
Thus GPS cannot be a good solution.

M. J. PIRAN ET AL. 921
3. Proposed Fixed Topology
In this section we see the topology th at we propose for a
network where we route the data safely to the Base Sta-
tion (BS) without the use of GPS. We assume that there
are two types of sensors in the network. The first kinds
of sensors are fixed sensors which are deployed on pre-
determined distances on both sides of the road (Road
Side Sensors). The second type of sensors is the sensors
that are attached to every car and which communicate
with the fixed roadside sensors (Vehicles’ Sensors).
Road Side Sensors (RSS) act as Cluster Head (CH) to
forward collected data from Vehicles’ Sensor (VS) to the
Base Station (BS) e.g. Police Station or Rescue Team
Station.
As we are trying to save cost of the network, the
number of RSS nodes is an important factor which is
depend on their communication coverage range and dis-
tances from each other.
Suppose each RSS node can cover up to 500 m, as the
Figure 2 depicted, each node can communicate with 3
other nodes. Therefore for each one kilometer we need 7
road side sensor nodes.
4. Routing Algorithm for the Proposed
Topology
In this algorithm we take that every vehicle will have a
sensor called Vehicle Sensor (VS) which has some pre-
determined attributes. We have sensors called Road Side
Sensors (RSS) on both sides of the road. The sensor in
the vehicle will constantly send astatus message for
every fixed time interval. The status message contains
the following attributes:
1) Vehicle ID.
2) Driver ID.
3) Spe ed of the vehicle.
4) Emergency status.
The Vehicle ID will contain the unique ID that is given
to every vehicle. Driver ID is the licence number
Figure 1. Schematic of the proposed topology.
Figure 2. RSS nodes communication coverage.
of the owner of the vehicle provided by the governing
authorities. The sensor in the vehicle (VS) senses the
current speed of the car and records it in the status mes-
sage. When the vehicle meets with an accident, the emer-
gency status attribute becomes active. The status mes-
sage sent by the vehicle will be received by the RSS.
When the emergency status is active or the speed of the
vehicle exceeded the base speed limit, the RSS forwards
the packet to the next RSS which is in its range of com-
munication. As shown in Figure 2, the RSS0 can send
data to the RSS1 and waiting for an acknowledgment, if
it didn’t received the acknowledgment packet in an in-
terval of time, then it sends the data packet to RSS2 and
it fails again, it will tries RSS3.
Meanwhile, the sender adds the information of the
nodes which did not responded to the data packet, as
failure nodes, so that the authorities investigate out of
service nodes and replace them if required.
As a vehicle is equipped with its own battery whose
capacity is much greater than that of a wireless sensor
node requires, there are no energy restrictions on the
sensor in the vehicle. But the RSS have no such power
source so we need to use their power efficiently. As we
have said, a primary concern of wireless sensor networks
is power consumption. It is desirable to place the net-
work devices in a low-power sleep mode as much as
possible, to minimize average power consumption. The
protocol in which the network devices monitor the chan-
nel constantly would be a poor choice for wireless sensor
networks, since their receivers would have to be con-
stantly active and drawing current (Due to their low
transmitter output power, the receivers of many wireless
sensor network devices dissipate more power than their
transmitters, exacerbating this situation.). Any energy
expended monitoring a silent channel, or listening to a
network device that does not have a message to send, is
wasted energy that could better be used for actual com-
munication.
So in our algorithm we keep some of our nodes in the
network sleep mode to save power. The decision whether
to stay awake or in sleep mode is decided by a probabil-
ity which is decided by the following factors:
1) Remaining energy in the sensor.
2) Generated random number.
3) Previous sate of the node.
4) Importance of t he m e ssag e.

M. J. PIRAN ET AL. 922
Remaining energy in the node will contribute in de-
ciding the state of the node. When the node has more
remaining energy then it can have high chances of being
awake and participate in the transmission.

Re
1mainingEnergy Prem TotalEnergy




(1)
A random number is generated and if the random
nu mbe r is above a th reshold level then the node will hav e
chances of being awake.



1
0
ifrand threshold
Prand ifrand threshold





(2)
Previous state of the node also affects the present state
of the node if the previous state is active then the node
tries to change its state.


1
0
ifpreviousstate awake
P stateifpreviousstatesleep
 



 (3)
Importance of the message also decides the state of the
node. If the node receives an important message like
emergency active attribute messages then it have higher
chances of being awake.
 

0
1
ifEMERGRNCY
Pimp otherwise





(4)
The total probability of a node to go to sleep mode is
 
0.25Pp imppstatep randp rem  


(5)
5. Applications of Proposed Work
5.1. Velocity Monitoring
As the RSS will know its position, the speed limit in that
particular location will be decided by the authorities and
fed in the sensor. Every vehicle moving continuously
sends status data packets and whenever an RSS detects the
velocity of a vehicle exceeding th e velocity limit, the da ta
is being forwarded to the next node and eventually to the
Base Station. The data specifies the approximate location
of the vehicle, vehicle’s ID and other information which is
useful for the governing authoriti es.
5.2. Positioning Information
When there is a need to know the location of a vehicle
—to find a stolen vehicle—we send a request query giv-
ing the vehicle ID. This is circulated throughout the net-
work and when an RSS gets a data packet from the
matching vehicle ID then its position and related infor-
mation is sent to the Base Station.
5.3. Incident and Accident Reporting
As we have discussed in the routing protocol when a car
remains stationary for longer periods of time or when a
car sends a panic message, it is immediately routed to the
Base Station—police station and rescue team. Since the
reported data contains all the important data like vehicle
ID and approximate position it is easy for the officials to
proceed forward accordingly.
6. Simulation Results
To simulate the topology in MATLAB, we generate
random traffic at different times all along the road. Then
using these results we plot the graph. The initial energy
in the network is assumed to be 10,000 units.
Figure 3 shows the remaining energy in the network
vs. the number of events occurred. This plot is given for
different transmission probabilities. Figure 4 shows the
Figure 3. Graph of Remaining Energy VS Number of events .
Figure 4. Graph of Packet Loss VS Number of events.

M. J. PIRAN ET AL. 923
Table 1. Value of energy remaining for the first 100 events.
Probability of transmission
/ parameter Remaining Energy in the network Packet loss
100% 5200 0
80% 8080 0
60% 8560 4
40% 8500 4
20% 9000 6
Table 2. Value of energy remaining for the first 200 events.
Probability of
transmission / parameter
Remaining energy
in the network
Packet
loss
100% 400 0
80% 1540 5
60% 2800 4
40% 5680 9
20% 6160 15
Packet loss vs. the number of events occurred. This is
also plotted for different transmission probabilities. So,
we should make a compromise for the energy consump-
tion and avoid packet loss.
From the above given tables we see that if the trans-
mission probabilities are decreased then energy remain-
ing in the network at any time is increased. But at the
same time we also need to consider the packet loss oc-
curring due to low transmission probability. Ta ble 1 and
Table 2 show the values of Energy remaining in the
network for first 100 events and 200 events respectively.
7. Conclusions
In this paper we discussed various aspects of communi-
cation in Vehicular Networks. We also saw an optimal
energy utilization algorithm for vehicular networks. The
proposed algorithm is free from GPS and i t doesn’t requi re
any costly topology to fi nd the l ocati on inform ation.
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