Minimum distance based routing protocol for lifetime improvement in wireless sensor network

IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 04 Issue: 06 | June-2015, Available @ http://www.ijret.org 298
MINIMUM DISTANCE BASED ROUTING PROTOCOL FOR LIFETIME
IMPROVEMENT IN WIRELESS SENSOR NETWORK
Mugdha A. Chaudhari1
, Sanjay V. Khobragade2
1
Electronics and Telecommunication Department, Dr. Babasaheb Ambedkar Technological University, Lonere,
Raigad, Maharashtra, India
2
Electronics and Telecommunication Department, Dr. Babasaheb Ambedkar Technological University, Lonere,
Raigad, Maharashtra, India
Abstract
Balanced utilization of energy of wireless sensor nodes is a challenge while designing wireless sensor network (WSN). This
energy of sensor node is a limited resource and measure for the lifespan of WSN. Communication process consumes most of the
energy of sensor node hence; energy of sensor node becomes a major design issue for WSN. Clustering is preferred while
designing routing protocols for WSN for its many to one traffic pattern. In our minimum distance based routing protocol for
lifetime improvement in WSN (MDBRP) clusters are formed once in a lifetime and their heads are selected rotationally based on
minimum communication distance between nodes and their next hop. MDBRP considers minimum energy consumption which
aims to increase the overall lifespan of WSN.
Keywords— clustering, dynamic clustering, routing protocol, static clustering, wireless sensor network.
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1. INTRODUCTION
Wireless sensor network (WSN) serves in many areas like
military surveillance, industrial automation, traffic
management, home automation, etc. Various improvements
in embedded system technology make it possible to provide
low cost, low power, small sized, multifunctional wireless
sensor nodes for such broad application areas. Due to the
improved features of these wireless sensor nodes over
traditional sensors WSN performed very well in various
applications mentioned in [1].
Limited battery power of wireless sensor nodes is critical
issue while designing and maintaining WSNs. Sensor nodes
depletes their energy while establishing routing path for data
transfer and mostly in communicating. Communication is
most energy consuming task for wireless sensor node [2].
The overall life period of WSN called as lifetime of WSN
depends entirely on energy of sensor nodes involved in
network. When the energy of sensor nodes goes down to zero
or below some threshold value set according to requirement
of network then that node is considered as dead. In paper [2]
lifetime is defined in two ways such as the time elapsed from
the start of network operation to the first death of any node
occurred or the time elapsed from the start of network
operation to the death of last node in the network. Due to
dependence of network’s lifetime on energy of sensor nodes
it becomes an important design aspect for researchers while
designing WSN. Now a day routing protocols are designed so
as to balance the energy consumption of sensor nodes to
improve lifetime of WSN. MDBRP protocol uses clustering
technique for routing characterized by static clusters and
dynamic cluster head selection. This protocol insures the
minimum communication distance for any node in the
network so as to minimize its energy consumption and hence
increasing network lifetime.
2. LITERATURE SURVEY
A survey about WSN and its applications is done in [3], [4]
which elaborates the details of WSN and its parts.
Architectural design issues and challenges are explained in
[3], [5], [6] which affects the performance of routing
protocols. WSN comes under the infrastructureless networks
characterized by distributed, low-power and randomly
deployed wireless sensor nodes. While developing routing
protocol for WSN these aspects have to be considered.
An overview of holes occurring in WSNs is described in [7]
stating the causes of creating holes in network. Hole in
WSNs is one of the serious design issues. Holes are created
when nodes get disabled because of any reason and cause
break in the routing path. Hence routing protocol designing
considers this as a challenge to overcome through with.
Hierarchical routing protocol based on clustering minimizes
the energy consumption of sensor node as in case of LEACH
[8]. This protocol operates in terms of round which is
considered as the time elapsed for delivery of data from each
and every node in the network to the final destination place.
Round split into setup phase and steady state phase. During
the set up phase cluster heads (CH) are elected among the
nodes in network according to threshold set previously.
When the heads are elected then remaining nodes decide their
respective nearest heads and forms the cluster. After then in
steady state phase; actual data transferred to the base station
(BS) along with the data fusion at CH.
LEACH-Centralized [9] is derived from LEACH where base
station does not allow less energy node to be elected as CH.
However in large scale network, nodes far away from BS are
unable to send their status to BS.

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3. NETWORK MODEL
The network model for this MDBRP protocol assumes all
nodes to be homogeneous with respect to their initial energy,
sensing capacity and processing ability. All nodes are
considered to be stationary, energy constraint and distributed
randomly in square field having base station at the very
center of field. The BS is assumed stationary with no limited
battery power. Every node in the network always has some
data to be sent. The network assumes complete data fusion at
BS and irrespective of the amount of data received at CH
every node transmits same amount of data. We consider the
time elapsed between the start of network to the death of last
node in the network as the lifetime of WSN.
4. MINIMUM DISTANCE BASED ROUTING
PROTOCOL (MDBRP)
Proposed MDBRP protocol satisfactorily provides
improvement in network lifetime of WSN. Hierarchical
clustering is applied in this MDBRP protocol where the
clusters remain constant throughout the network operation
called as static clustering. The cluster heads are selected
rotationally based on minimum communication distance
between node and its next hop. Such static clustering assures
no coverage holes in network while dynamic CH selection
ensures balanced energy dissipation among the nodes. The
data fusion is achieved at the CH so as to minimize overhead.
4.1 Formation of Clusters
The first step of MDBRP protocol is to form clusters by
dividing network area after the nodes and BS is deployed
randomly. The squared network area is divided into n number
of concentric squares. This value of n depends on the
distance assumed between two concentric squares (d) which
is selected so as to balance the clusters in terms of their area.
The value of n can be found from the following equation.
𝑛 =
𝐶𝑝 𝑥
𝑑
Where, Cp(x) is x co-ordinate of center point (BS) of network.
Value of n gets increased when network area is expanded.
The coordinates of these squares are obtained with the help
of distance from the base station to the nth
square is given by
following equation
𝑑 𝑛 = 𝑛 × 𝑑
Using this distance dn we obtain the coordinates of squares as
follows:
𝑇𝑟 𝑆𝑛 = 𝐶𝑝 𝑥 + 𝑑 𝑛 , 𝐶𝑝 𝑦 + 𝑑 𝑛
𝑇𝑙 𝑆𝑛 = 𝐶𝑝 𝑥 − 𝑑 𝑛 , 𝐶𝑝 𝑦 + 𝑑 𝑛
𝐵𝑙 𝑆𝑛 = 𝐶𝑝 𝑥 − 𝑑 𝑛 , 𝐶𝑝 𝑦 − 𝑑 𝑛
𝐵𝑟 𝑆𝑛 = 𝐶𝑝 𝑥 + 𝑑 𝑛 , 𝐶𝑝 𝑦 − 𝑑 𝑛
Where, Sn is nth
square, Tr is top right corner of square, Tl is
top left corner of square, Bl is bottom left corner of square, Br
is bottom right corner of square.
In next step the space between two concentric squares is
further divided into equal area quadrilaterals as shown in
figure 1 denoted as R1 through R9. The inner square is very
small in area so kept as a single cluster (R1). Co-ordinates of
all regions as shown in figure1 are obtained using equation
below:
𝐿𝑜𝑐𝑎𝑡𝑖𝑜𝑛 = 𝐶𝑝 𝑥 ± 𝑑 𝑥 , 𝐶𝑝 𝑦 ± 𝑑 𝑦
Where Location is any corner of cluster R1 through R9, dx
and dy are distances of corner from base station in X and Y
directions.
Fig. 1 Formation of clusters
4.2 Cluster Head Selection
To achieve the equal energy dissipation MDBRP protocol
selects CH at every round. CH selection is based on
minimum communication distance for each node from the
reference point of that cluster. The reference point for each
cluster is the center of that cluster which is not the same for
inner region R1 as it has minimum area. Nodes in other
region (R2 through R9) compare their distance from
reference point and the minimum distant node is selected as
CH for the current round. The next minimum distant node is
selected as CH for next round and so on. Nodes in R1 select
BS as their next hop.
4.3 Data Transmission
In each round of protocol operation first CHs are selected
then data transmission takes place. In this MDBRP protocol
communication takes place in two levels of hierarchy. First
level communication takes place for regions R1 through R5.
The nodes in R1 send their data directly to base station. CH
of regions R2 through R5 first aggregate their own data along
with the data collected from their cluster members and then

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send the fused data to BS. In second level of communication
CHs of region R6 through R9 sends their aggregated data to
their respective next-hops which are R2 through R5
respectively.
5. SIMULATION RESULT
We perform MATLAB simulation for minimum distance
based routing protocol and compare our results with that of
LEACH protocol. In our network model 120 homogeneous
wireless sensor nodes are randomly deployed across square
area of 120 m × 120 m having BS at centre. The radio
parameters are taken same as that of LEACH [3], [4]. The
packet size is considered of 2000 bits.
We evaluate MDBRP protocol for network lifetime as
defined in network model, throughput and average residual
energy of network.
Fig. 2 Network lifetime
Fig. 3 Residual energy
In figure 2 our protocol has maximum alive nodes as
compared to LEACH, which means enhanced lifetime of
network also the average residual energy of network can be
seen more as compared to LEACH in figure 3. Throughput of
the network means number of packets send to base station
which are more in case of our MDBRP protocol as in figure 4.
Fig. 4 Throughput
6. CONCLUSION
In our work we used hierarchical routing, static clustering
and dynamic cluster head selection based on minimum
communication distance which will enhance the lifetime of
wireless sensor network. Static clustering minimizes the
problem of coverage hole by maintaining optimum numbers
of clusters. Energy consumption is directly proportional to
communication distance hence CH selection according to
minimum communication distance effectively utilizes the
limited battery power of sensor nodes. Ultimately this project
work will take a step towards satisfying the need of energy
efficient architectural routing technique so as to maximize
lifetime of wireless sensor network.
REFERENCES
[1] Mohd Fauzi Othman and Khairunnisa Shazali,
“Wireless Sensor Network Applications: A Study in
Environment Monitoring System”, in International
Symposium on Robotics and Intelligent Sensors, by
Elsevier, 2012.
[2] Zhao Han, Jie Zhang, Liefeng Liu and Kaiyun Tian,
“A General Self-Organized Tree-Based Energy-
Balance Routing Protocol for Wireless Sensor
Network”, IEEE Transactions on Nuclear Science, vol.
61, no. 2, pp. 732-740, April 2014.
[3] Jennifer Yick, Biswanath Mukherjee, Dipak Ghosal,
“Wireless sensor network survey”, International
journal on computer networks by Elsevier, vol. 52, pp.
2292-2330, 2008.
[4] F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E.
Cayirci, “Wireless sensor networks: a survey,”
Computer Networks, vol. 38, no. 4, pp. 393–422, 2002.

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[5] Ajay Jangra and Swati, “Wireless Sensor Network
(WSN): Architectural Design issues and Challenges”,
International Journal on Computer Science and
Engineering, vol.02, no.09, pp.3089-3094, 2010.
[6] Sanatan Mohanty, “Energy Efficient Routing
Algorithms for Wireless Sensor Networks and
Performance Evaluation of Quality of Service for
IEEE 802.15.4 Networks”, M. Tech. dissertation,
National Institute of Technology, Rourkela, India,
January, 2010.
[7] Rajat Bhardwaj, Hitesh Sharma, “Holes in wireless
sensor networks”, International Journal of Computer
Science and Informatics (IJCSI), vol-02, Iss-4, pp.
2231–5292, 2012.
[8] Wendi Rabiner Heinzelman, Anantha Chandrakasan,
and Hari Balakrishnan, “Energy-Efficient
Communication Protocol for Wireless Micro-sensor
Networks”, in IEEE Proceedings of the 33rd Hawaii
International Conference on System Sciences, 2000.
[9] Wendi Rabiner Heinzelman, Anantha Chandrakasan,
and Hari Balakrishnan, “An Application-Specific
Protocol Architecture for Wireless Micro-sensor
Networks”, IEEE transactions on wireless
communications, vol. 1, no. 4, October 2002.

Minimum distance based routing protocol for lifetime improvement in wireless sensor network

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Minimum distance based routing protocol for lifetime improvement in wireless sensor network