Wireless Sensor Network, 2009, 1, 350-357
doi:10.4236/wsn.2009.14043 Published Online November 2009 (http://www.scirp.org/journal/wsn).
Minimization of Collision in Energy Constrained
Wireless Sensor Network
Moses Nesa SUDHA1, Muniappan Lakshapalam VALARMATHI2, George RAJSEKAR1,
Michael Kurien MATHEW1, Nagarajan DINESHRAJ1, Sivasankaran RAJBARATH1
1Karunya University, Coimbatore, India
2Government College of Technology, Coimbatore, India
Received May 13, 2009; revised July 20, 2009; accepted July 27, 2009
Abstract
Wireless Sensor Networks (WSNs) are one of the fastest growing and emerging technologies in the field of
Wireless Networking today. The applications of WSNs are extensively spread over areas like Military, En-
vironment, Health Care, Communication and many more. These networks are powered by batteries and
hence energy optimization is a major concern. One of the factors that reduce the energy efficiency of the
WSN is collision which occurs due to the high density of data packets in a typical communication channel.
This paper aims at minimizing the effects of congestion leading to collision in the network by proposing an
effective algorithm. This can be done by optimizing the size of the contention window by introducing pa-
rameters like source count and α. If the contention window of a node is low, it results in collision. If the size
of the contention window of a node is high then it results in a medium access delay. Thus minimizing colli-
sion and medium access delay of data packets conserve energy.
Keywords: Energy, Collision, Contention Window, Wireless Sensor Networks
1. Introduction
Wireless Sensor Networks (WSNs) are a typical type of
wireless networks consisting of a large number of sensor
nodes. WSNs are undoubtedly one of the largest growing
types of networks today. They are fast becoming one of the
largest growing networks today and, as such, have attracted
quite a bit of research interest. They are used in many as-
pects of our lives including environmental analysis and
monitoring, battlefield surveillance and management,
emergency response, medical monitoring and inventory
management. These networks also play a significant role in
areas like agriculture and industries as well. Their reliabil-
ity, cost-effectiveness, ease of deployment and ability to
operate in an unattended environment, among other posi-
tive characteristics, make sensor networks the leading
choice of networks for these applications.
Much research has been done to make these networks
operate more efficiently including the application of data
aggregation. A wireless network normally consists of a
large number of distributed nodes that organize them-
selves in an ad-hoc fashion. Each node has one or more
sensors, embedded processors and low power radios
which are normally battery operated. Unlike other wire
less networks, it is generally difficult or impractical to
charge/replace exhausted batteries. That is why the pri-
mary objective in wireless sensor networks design is
maximizing node/network lifetime, leaving the other
performance metrics as secondary objectives. Various
factors like concurrent transmissions, buffer overflows
and dynamically time varying wireless channel condi-
tions lead to the concept of Congestion [1]. Collision has
the following drawbacks: 1) increase energy dissipation
rates of sensor nodes, 2) causes a lot of packet loss,
which in turn diminish the network throughput and 3)
hinders fair event detections and reliable data transmis-
sions [2,3]. Congestion control or congestion avoidance
has thus become very crucial for effective transmission
of data packets [4]. The main reason of congestion in
WSN, is allowing sensing nodes to transfer as many
packets as they can [2]. Hence it can be inferred that,
congestion in wireless networks leads to collision be-
tween the packets transmitted. Collision occurs when
two nodes send data at the same time, over the same
transmission medium or channel. Medium Access Con-
trol (MAC) Protocols have been developed to assist each
node to decide when and how to access the channel
[1–10]. However, the medium- access decision within a
dense network composed of nodes with low duty-cycles

M. N. SUDHA ET AL. 351
is a challenging problem that must be solved in an en-
ergy-efficient manner. Keeping this in mind, emphasis is
first given to the peculiar features of sensor networks,
including reasons for potential energy wastage at me-
dium-access communication and how they can be mini-
mized.
2. Priority Based MAC Protocol
2.1. Configuration Requirements
First the topology of the entire Wireless Sensor Network
(WSN) is set as required. The MAC type used here is
802.11. For transmission and reception of data packets to
take place in a WSN, there is a need to have a source
node, the transmission paths to be followed, and a sink
node. Source nodes can vary but sink nodes are fixed
once the transmission of data packets occur. The final
collection of the transmitted data occurs at the sink node.
This collected data is taken and used according to the
application needed. Apart from this various other pa-
rameters like transmission range, packet size, sink loca-
tion, data rate, simulation time and initial energy are all
given as initial settings along with the topology forma-
tion.
2.2. Calculation of Sensing Nodes (Ns)
Ns is the approximate number of nodes within the sens-
ing radius of a particular event. We consider a network
of N sensing nodes, deployed with uniform random dis-
tribution over an area A. The Node density is defined as
ρ = N/A. And Ns is calculated as,
Ns =π ρ R
s
2 (1)
where, Rs is the sensing range of each node. A single
sink node in the network placed anywhere within the
terrain is taken into consideration. Mobile sensors which
form a dynamic ad-hoc network are not considered. All
sensing nodes considered are static and the network is
homogeneous i.e., all nodes have the same processing
power and equal sensing and transmission range. Data
generation rate of each sensing node is also assumed to
be equal.
2.3. Priority Based Source Count
Source Count value of any node i, denoted as SCi, is de-
fined as the total number of nodes to which it is able to
forward data. In other words, it is the number of down-
stream nodes for a particular node, which responds to the
advertisement of the node. Since a downstream node
requires knowing its Source Count (SC) value whenever
it has some data packets to send, it is sufficient to propa-
gate SC value along with the data packet. While trans-
mitting data packets, each upstream node inserts its SC
value in the packet header and the downstream node can
easily obtain its SC value. An upstream node learns the
SC value of its downstream by snooping packets trans-
mitted by the latter. Note that, a transient state exists
between the event occurrence and the stabilization of SC
values of all downstream nodes. SC value of a down-
stream node is stabilized whenever it receives at least
one packet from all of its upstream nodes and therefore
the network enters into steady state when the sink node
receives at least one packet from each source node. Since
the duration of transient state is very short (less than a
second in our simulation), the effectiveness of the pro-
posed protocol is not hampered. It is notable that, SC
values of each node along the routing path are updated
without transferring any additional control packets. This
SC parameter works as a driving entity for all schemes of
our proposed protocol. Thus the SC values for all the
nodes that are involved in transmission and receptions of
data packets are calculated. With the help of these values
the priority of transmission is assigned to each node.
This helps in minimizing the collision in the Wireless
Sensor Network.
2.4. Calculation of Contention Window
Contention Window is a parameter which depends on
time [1]. It determines the rate of flow of data packets
and medium access delay. Now the Contention Window
value is calculated for each node that is involved in the
communication process. It is calculated as follows:
W (i) = CWmin x (Ns/Sci ) (2)
where, W (i)-Contention Window value for any node i,
CWmin-Minimum Contention Window value, Ns- Ap-
proximate number of nodes within the sensing radius of a
particular event, Sci-Source Count value of any node i.
2.5. Inclusion of α Parameter
The parameter α is a scaling factor that is introduced in
Equation (2) to optimize effects of collision and medium
access delay. It ranges from 0.1 to 2 based on channel
contention.
W (i) = CWmin x (Ns / Sci ) x (1/ α ) (3)
If the number of contending neighbors of a transmit-
ting node is very low, lower value of α simply increases
the medium access delay and reduces the network
throughput. On the other hand, if the number of con-
tending neighbors of a transmitting node is very high, a
higher value of α increases the collision probability and
thereby increases packet loss. The value of α is initial-
ized to 1, which nullifies its effect. Later on, to ensure
efficient medium utilization, the value of α is set care-
fully. A sharp increase or decrease of the value of α may

352 M. N. SUDHA ET AL.
also hinder the throughput of the network. Sections 3.1
and 3.2 describe the variation of α.
2.6. Idealization of Contention Window
The limitation of Equation (2) is that the contention win-
dow cannot be varied for different number of data pack-
ets. But we know that window size is directly propor-
tional to packet size and inversely proportional to data
rate. Hence we have another equation:
W (i) = (Packet size x No. of data packets)/Data rate
(4)
Equation (4), is used to vary the α value in Equation (3)
and thereby an optimized contention window is obtained
in order to minimize the effects of collision and delay, in
the process of communication, simultaneously.
2.7. Idle Listening
In the above sections, the effect of collision and some
parameters associated with it have been analyzed. In this
section, another factor has been taken into account which
leads to some amount of energy loss in MAC protocols -
idle listening [11]. Since a node does not know when it
will be the receiver of a message from one of its
neighbors, it must keep its radio in receive mode at all
times. So it loses energy as long as it is ON. Hence, the
nodes which do not take part in the communication, loses
energy due to idle listening. Here in this paper, this phe-
nomenon has been considered in Sections 2.8 and 3.3. As
a result, a particular amount of energy is conserved and
better energy efficiency is obtained for each node in the
network.
2.8. Evaluation with Idle Listening
In this paper, each node in the network is enabled when
it receives or transmits data packets. If a node does not
involve in communication, it is disabled, whereby no
further transmission or reception of data packets take
place. The amount of energy lost by keeping a node in
the ON state is approximately 50–100% of the receiving
energy. In the scenarios explained in Sections 3.1 and 3.2,
the energy loss due to the node being in the ON state is
66% of the receiving energy. When the nodes that are not
involved in the communication process are disabled, this
energy is saved and we obtain higher energy efficiency.
3. Energy Analysis
In the above sections, we have discussed about the phe-
nomenon of contention window and idle listening. In this
section, we will discuss two scenarios in which the con-
tention window is varied to consider the effects of colli-
sion and medium access delay.
3.1. Scenario 1
In the first scenario, we have eight nodes placed in a
randomly chosen topology. The simulation would be
carried out according to the parameters mentioned in the
above table. Here we would consider the effect of colli-
sion for each node in the network.
Using the specifications given in Table 2, data packets
are transmitted. Here the data packets are very high in
number and so when they are transmitted, collision oc-
curs. In order to minimize the collision, we vary the con-
tention window by decreasing α value. By doing so the
contention window size is increased and thereby colli-
sion is minimized. This variation of α is done by keeping
the value of contention window obtained from Equation
(3) as reference.
Table 1. Simulation parameters.
Parameter Value
Total Area 500 x 500
Number of nodes 8
MAC Type 802.11
Initial Energy 5 Joule/Node
Transmission Energy 0.0005 Joule/Node
Reception Energy 0.0003 Joule/Node
ON-Time Energy 0.0002 Joule/Node
Data Rate 10 Bytes/s
Packet Size 64 Bytes
Initial α Value 1
Range of α Value 0.1 ~ 2
Simulation Time 150 ms
Table 2. Source count and No. of packets.
Node Source Count No. Of Packets
0 3 10
1 3 12
2 2 4
3 1 18
4 1 11
5 4 9
6 5 7
7 5 12

M. N. SUDHA ET AL. 353
Using the specifications given in Table 2, data pack-
ets are transmitted. Here the data packets are very high
in number and so when they are transmitted, collision
occurs. In order to minimize the collision, we vary the
contention window by decreasing α value. By doing so
the contention window size is increased and thereby
collision is minimized. This variation of α is done by
keeping the value of contention window obtained from
Equation (3) as reference.
Figure 1 is a diagrammatic representation which shows
that, more number of data packets is sent within the lim-
ited time frame and as a result, collision is occurring.
W(i)= Wmin x (Ns/SCi) x (1/α) (5)
3.2. Scenario 2
In the second scenario, we have eight nodes placed in a
randomly chosen topology. The simulation would be
carried out according to the parameters mentioned in
Table 3. Here, the effect of medium access delay for
each node in the network is considered. The number of
packets transmitted by each node would be lesser than
the number considered in the first case of collision.
Using the above specification, data packets are trans-
mitted. Since they are very less in number medium ac-
cess delay occurs. In order to minimize this delay, we
vary the contention window by increasing the α value.
By doing so the contention window size is decreased and
thereby medium access delay is minimized. This varia-
tion of α is done by keeping the value of contention
window obtained from Equation (3).
Figure 1. Collision of packets when contention window size
is small.
Table 3. Source count and No. of packets.
Node Source Count No. Of Packets
0 3 2
1 3 2
2 2 3
3 1 6
4 1 6
5 4 1
6 5 1
7 5 1
Figure 2. Medium access delay in the network when con-
tention window size is large.
Figure 2 is a diagrammatic representation which
shows that, less number of data packets is sent within
the large time frame and as a result, medium access de-
lay is occurring.
W(i)= Wmin x (Ns/SCi) x (1/α) (6)
3.3. Conclusion of Energy Analysis
In Scenario 1, to minimize the effect of collision, the
size of the contention window is increased by decreasing
the α value. In Scenario 2, to minimize the effect of me-
dium access delay, α value is increased. This results in
minimizing the medium access delay.
Thus taking into account whether collision occurs or
medium access delay occurs, α value is varied and
thereby the contention window is also varied. Thus an
idealized contention window required for the communi-
cation process is obtained which will minimize the ef-
fect of collision and medium access delay to a greater
extent, producing high efficiency.
In the above 2 cases energy loss due to idle listening
is reduced. This is achieved by disabling the nodes when
transmission and reception of data packets do not occur.
However, the energy conserved in the above scenarios
was observed to be considerably less. Further analysis
can be done on implementing a better algorithm to re-
duce the effect of idle listening.
Figure 3. Optimized contention window in order to mini-
mize both collision and medium access delay.

354 M. N. SUDHA ET AL.
Figure 3 is a diagrammatic representation which
shows the ideal condition that the data packets is sent
within the idealized time frame and as a result collision
and medium access delay is minimized to a great extent.
4. Results
Considering the above mentioned topology and simula
Figure 4. Flow-diagram which explains the flow of the
entire process of the proposed protocol.
tion parameters two cases have been analyzed. In the
first case the effect of collision has been minimized and
in the second case, the phenomenon of medium access
delay has been dealt with. Thus we try to obtain an ideal
contention window size whereby both these effects are
dealt with effectively. The implementation of the fol-
lowing scenarios have been done in Network Simulator-
2 (Ns-2), version 2.28 [12].
4.1. Scenario 1
Here in this scenario, consider that each node in the net-
work has a higher number of packets to send to the
downstream nodes in the network. Due to this, the con-
tention window would be small and thus its size been
increased. Thus it has been found that the collision is
minimized effectively. As a result, the energy lost in
each node has been reduced. Furthermore, a small
amount of energy has been conserved by reducing idle
listening.
It has been observed that, though the collision has
been minimized, a very small medium access delay oc-
curs with each node in the network.
Table 4. Results considering collision.
Energy Remaining in Node
Node With-ou
t SC
With
SC
With SC
& CW
With SC, CW and
Idle listening
0 4.7049 4.73494.7899 4.7919
1 4.7329 4.76794.8329 4.8349
2 4.8634 4.91094.9159 4.9199
3 4.8574 4.85744.9324 4.9374
4 4.8384 4.89194.9219 4.9259
5 4.7529 4.79794.8479 4.8499
6 4.7849 4.87294.9129 4.9269
7 4.6874 4.80144.8714 4.8764
Figure 5. The source count value for each node.

M. N. SUDHA ET AL. 355
Figure 6. The initial contention window and idealized con-
tention window for each node.
Figure 7. The α value which has been reduced due to the
collision which occurs in each node.
Figure 8. The collision occurring and the collision which has
been minimized for each node.
Figure 9. The delay occurring after obtaining the ideal size
for the contention window for each node.
Figure 10. The energy lost comparison for each node after
applying the various cases.
Table 5. Results considering medium access delay.
Energy Remaining in Node
Node Without SCWith SC With SC &
CW
With SC, CW
and Idle lis-
tening
0 4.7049 4.7899 4.7899 4.7919
1 4.7329 4.8329 4.8329 4.8349
2 4.8634 4.9159 4.9159 4.9199
3 4.8574 4.9329 4.9324 4.9374
4 4.8384 4.9219 4.9219 4.9259
5 4.7529 4.8479 4.8479 4.8499
6 4.7849 4.9129 4.9129 4.9269
7 4.6874 4.8714 4.8714 4.8764

356 M. N. SUDHA ET AL.
Figure 11. The graph above shows the initial contention win-
dow size and the idealized contention window for each node.
Figure 14. The energy lost comparison for each node after
applying the various cases.
Figure 12. The α value which has been reduced due to the
collision which occurs in each node.
Figure 13. The graph above shows the initial delay and the
minimized delay for each node.
4.2. Scenario 2
In this scenario, consider that each node in the network
has a smaller number of packets to send to the down-
stream nodes in the network. Due to this, the contention
window would be larger than required and thus its size
has been reduced. The contention window size is varied
in such a way that the medium access delay becomes
negligible and collision is avoided.
It has been observed that, medium access delay has
been minimized and along with effects of collision. This
has helped in increasing the throughput of the network.
Furthermore the effect of idle listening and the energy
loss caused by it has been dealt with.
5. Conclusions
In this paper, a novel method of minimization of colli-
sion and medium access delay is introduced to reduce the
loss of energy of the nodes in the network. Here a Source
Count value is considered for each node, in order to re-
duce the collision of packets in the network. The Source
Count value prioritizes the transmission of packets from
each node, whereby the collision of data packets and
medium access delay associated with each node during
communication process are minimized. The Contention
Window size is calculated in accordance with Source
Count values assigned for each node. The initial effi-
ciency of the WSN was found to be around 70%. After
applying the various parameters to minimize collision
and medium access delay, the efficiency was increased to
around 85-90%. Hence a substantial amount of energy
can be saved through this method. Without optimizing on
idle listening, the efficiency was found to be around
82%.

M. N. SUDHA ET AL. 357
Though the idealized contention window size has been
calculated, the chances of collision and medium access
delay may still prevail in a minimal amount in the net-
work. Hence it should be noted that a MAC protocol
needs to be introduced which could eliminate the effects
of collision and medium access delay simultaneously.
Also the energy conserved by minimizing idle listening,
can further be improved.
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