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Australian Journal of Information Technology and Communication Volume II Issue I
ISSN 2203-2843
Enhancement in Divide and Conquer Scheme to
increase the Lifetime of Networks
Jagpreet Singh[1], Sarabjit Kaur[2]
Computer and Science Engineering, Punjab Technical University
Jalandhar, Punjab, India
[1]
[2]
[email protected]
[email protected]
Abstract- Within the last two decades, communication
advances have reshaped the way we live our daily lives.
Wireless communications has grown from an obscure,
unknown service to a ubiquitous technology that serves almost
half of the people on Earth. Wireless sensor network consists
of sensor nodes which are powered by battery; to communicate
with each other for environment monitoring. Energy
efficiency is the main issue in wireless sensor networks. From
energy conservation perspective in Wireless Sensor Networks
(WSNs), clustering of sensor nodes is a challenging task.
Clustering technique in routing protocols play a key role to
prolong the stability period and lifetime of the network .In this
paper, i use a new routing protocol for WSNs. The Divideand-Rule (DR) is based upon static clustering and minimum
distance based Cluster Head (CH) selection technique. This
technique selects fixed number of CHs in each round instead
of probabilistic selection of CH. Simulation results show that
DR protocol outperforms its counterpart routing protocols.
Keywords- Wireless Sensor Networks (WSNs), Divide and
Rule Scheme, Research Methodology and Results.
I.
INTRODUCTION
Wireless Sensor Networks (WSNs) have been widely
considered as one of the most important technologies for
the twenty-first century. A wireless sensor network is a
type of wireless network. A wireless sensor network is a
wireless network that made up of a number of sensors
node and at least with one base station. In wireless
network a collection of nodes organized in a cooperative
network. Energy saving is the crucial issue in designing
the wireless sensor networks. In order to maximize the
lifetime of sensor nodes, it is preferable to distribute the
energy dissipated throughout the wireless sensor network.
Wireless sensor network has two types-structured and
unstructured. In structured wireless sensor network, the
all sensor nodes are deployed in pre designed manner. In
unstructured a collection of sensor nodes deployed in ad
hoc manner into a region. Once deployed, the network is
absent unattended perform monitoring and reporting
functions. The benefit of structure wireless sensor
network is that some nodes can be deployed with lower
network maintenance and management cost. Fewer nodes
can be deployed at specific locations to provide coverage
while ad hoc deployment can have uncovered regions.
Sensor nodes are collecting data about environment, after
collecting it they process it and then transmit to the base
station. Base station provides an interface between user
and internet. Basic characteristic of the wireless sensor
network are limited energy, dynamic network topology,
lower power, node failure, mobility of the nodes, shortrange broadcast communication, multi-hop routing and
large scale of deployment. Energy consumption and
network life time has been considered as the major issues
in wireless sensor network (WSN). In wireless sensor
networks the size and cost of the sensor nodes may vary
from micro to macro and from one to few hundred dollars
respectively. In WSN, the main problem is that the
battery cannot be replaced but the main source while
sensor nodes sense the data is battery power even sensor
nodes also contain such resources which are
irreplaceable. So, therefore there is need to design an
energy-efficient technique which enhance the lifetime of
wireless sensor network. Wireless sensor networks follow
some approaches for improving the lifetime of battery
like energy-aware technique, multi-hop routing and
density control technique but these approaches still need
to be improved. On the basis of network structure, routing
protocol is divided into three parts: flat routing protocol,
Hierarchical routing protocol and location aware. In flat
all the nodes have same rules i.e. sensing the environment
and sending the data to the base station. So it has very
low network lifetime. In hierarchical the low energy
nodes sense the environment and high energy nodes used
to send the data to the base station. Location based
routing can be used in networks where sensor nodes are
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Australian Journal of Information Technology and Communication Volume II Issue I
able to determine their position using a variety of
localization system and algorithm.
II. RELATED WORK
Peyman Neamatollahi et al. [1] explained that clustering
is an effective approach for organizing the network into a
connected hierarchy, load balancing, and prolonging
network lifetime. Clustering protocols in wireless sensor
networks are classified into static and dynamic. In static
clustering, clusters are formed once, forever and role of
the cluster head is scheduled among the nodes in a
cluster. However, in dynamic clustering the time is
divided into rounds and clustering is performed in the
beginning of each round. This paper presents a Hybrid
Clustering Approach (HCA).
Jakob Salzmann et al. introduced [2] a large wireless
sensor networks, low energy consumption is a major
challenge. Hence, deployed nodes have to organize
themselves as energy efficient as possible to avoid
unnecessary sensor and transceiver operations. The
energy conserving operations are limited by the task of
the network; usually the network has to guarantee
complete functionality during its lifetime. The
contribution of this paper completes the functionalityaware and energy-efficient clustering algorithm family
MASCLE by two Innovative algorithms.
K. Latif et. al. [3] have presented routing technique called
Divide-and-Rule which is based on static clustering and
minimum distance based Cluster Head selection. Network
area is logically divided into small regions (clusters). Old
fashioned routing techniques such as LEACH, LEACH-C
are not as energy efficient as present day clustering
techniques such as Divide-and-Rule scheme. The benefit
of Divide-and-Rule scheme is that when it is compared
with LEACH and LEACH-C this scheme provides better
results in terms of stability period, network life time, area
coverage and throughput. But the limitation of this
scheme is that during routing each node in Os region
sends its data to Primary level Cluster Heads which then
forwards the aggregated data to the secondary level
Cluster Head present in the Ms, Secondary level Cluster
Heads then, aggregate all collected data and forward it to
Base Station which will lead to more energy consumption
of CH nodes present in the Middle Square and Inner
Square regions which may lead to energy hole and may
cause data routing problems.
Basilis Mamalis et.al [4] describes the concept of
Clustering and described various design challenges of
clustering in Wireless Sensor networks. The paper also
describes various clustering Protocols including
Probabilistic Clustering Approaches and Non-
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Probabilistic Clustering Approaches. The algorithms
discussed in these protocols consider periodically reelection of Cluster Heads (rotation of Cluster Head role)
among all nodes. The main drawback of these algorithms
is that the time complexity of these algorithms is difficult
to be kept low as the size of the Wireless sensor
Networks becomes larger and larger, the extension in
multi-hop communication patterns is unavoidable which
increases the routing path.
Kiran Maraiya et.al [5] has presented an overview of
wireless sensor network, how wireless sensor networks
works and various applications of wireless sensor
networks. In this paper it has been described that
characteristics of wireless sensor network are dynamic
network topology, lower power, node failure and mobility
of nodes, short-range broadcast communication and
multi-hop routing and large scale of deployment. But low
power of sensor nodes is one of the limitation of wireless
sensor network as in harsh environments it is difficult to
replace sensor nodes so low power may cause energy hole
in wireless sensor networks. Also multi-hop routing may
cause more nodes deplete their energy while routing as
compared to single hop routing.
III. DIVIDE AND CONQUER SCHEME
3.1 Background
Spatially dispersed wireless sensor nodes and one or more
Base Stations (BSs) are embodied to form WSN. Sensor
nodes keep an eye on the physical or environmental
conditions at different locations, and communicate
efficiently with BS. Typically, all the nodes equipped
with low power whereas base station occupy high power.
Applications of WSNs are in defense monitoring
operations, predicting environment conditions, traffic
control, health applications etc.
Today’s research challenge in WSNs is coping with low
power communication. Routing protocols in this regard
plays a key role in efficient energy utilization. In sending
data from node to BS, selection of a specific route, which
tends to minimize the energy consumption, is necessary.
Old fashioned routing techniques are not as energy
efficient as present day clustering techniques. LEACH,
LEACH-Centralized and Multi-hop. LEACH are few of
the earlier techniques of cluster based routing protocols
for WSNs. Basically two types of clustering techniques
exist; static clustering and dynamic clustering. Clusters
once established and never be changed throughout
network operation are known as static clusters, while
clusters based on some sort of network characteristics and
are changing during network operation are known as
dynamic clusters.
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Australian Journal of Information Technology and Communication Volume II Issue I
3.2 Introduction
Divide-and-Rule scheme [3] is based on static clustering
and minimum distance based Cluster Head selection.
Network area is logically divided into small regions
(clusters). The beauty of this technique is the formation of
square and rectangular regions, which divides the
network field into small regions, as a result the
communication distance for intra cluster and inter cluster
reduces.
a.) Formation of regions:
In first step, network is divided into n equal distant
concentric squares. For simplicity, take n = 3 here
therefore, network is divided into three equal distance
concentric squares: Internal square (Is), Middle square
(Ms) and Outer square (Os).
BS is located in the centre of network field therefore; its
coordinates are taken as reference point for formation of
concentric squares.
Division of network field into concentric squares can be
obtained from following equations:
Coordinates of top right corner of Is, Tr (Is)
Tr
(Is)
=
(Cp(x)
+
d,
Cp(y)
+
d)
(1)
Coordinates of bottom right corner of Is, Br (Is)
Br
(Is)
=
(Cp(x)
+
d,
Cp(y)
(2)
−
d)
Coordinates of top left corner of Is, Tl (Is)
Tl
(Is)
=
(Cp(x)
−
d,
Cp(y)
(3)
+
d)
Coordinates of bottom left corner of Is, Bl (Is)
Bl
(Is)
=
(Cp(x)
−
d,
Cp(y)
−
d)
(4)
Where, d is the factor of distance from center of network
to boundary of Is value of d for Ms and Os increases with
a multiple of 2 and 3 respectively. If there are n number
of concentric squares then the coordinates of nth square
can be found, Sn from the following equations.
Tr (Sn) = (Cp(x) + dn, Cp(y) + dn)
(5)
Br(S n) = (Cp(x) + dn, Cp(y) − dn)
(6)
Tl(S n) = (Cp(x) − dn, Cp(y) + dn)
(7)
Bl(S n) = (Cp(x) − dn, Cp(y) − dn)
(8)
•
In the second step, the area is divided into two concentric
squares into equal area quadrilaterals; latter is named as
Corner Regions (CR) and Non-Corner Regions (NCR).
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Fig 3.1 Divide and Rule regions formation
IV. RESEARCH METHODOLOGY
The communication between sensor nodes to sink is
based upon multi-hop communication. The power of the
sensor nodes positioned near the base station will exhaust
very fast as compared to those that are far away from
inner region. This happens because all the transmissions
done through sensor-to-sink paths, heavier load and
therefore consume more energy which ruin network
performance. Researchers have developed many energy
models but these models still need to be improved.
Clustering technique in routing protocols plays an
important role to increase the throughput, stability period
and network lifetime. Divide and Rule is one of the
scheme which based on static clustering and it is a energy
efficient routing protocol for wireless sensor network.
The sensor nodes which are placed near base station
communicate with base station and intermediate nodes
nevertheless utilize more energy. The communication
stops when batteries of the nodes near sink dead. Because
base station can communicate with nodes placed in the
other regions only with the help of nodes located near it.
To overcome with this problem relay nodes will be
introduced in the inner region, which have minimum
resource and high battery power. In the planned work, we
will place N number of relay nodes in the inner region to
communicate with the nodes in middle and outer region.
V. SIMULATION RESULTS
With the help of Network Simulation (NS-2) we
generated the network with 41 nodes. The simulation
result has been taken out in the NS-2 tool. There are
number of packets shown on y-axis and time is given on
x-axis in seconds.
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Australian Journal of Information Technology and Communication Volume II Issue I
ISSN 2203-2843
Fig 5.1 Delay
The fig. 5.1 shows the experimental results of Delay of
packets. Which are very less as compared to previous
author’s result.
Fig 5.3 Throughput
The fig.5. 3 show the experimental results of throughput.
VI. CONCLUSION
Fig 5.2 Packet Loss
The fig. 5.2 shows the experimental results of Packet loss.
For the packet loss the experimental results of the
proposed novel technique are better than the existing
technique.
With decreasing costs and advancing network lifetime of
Wireless Sensor Networks the number of potential
application areas is on the rise. To achieve both, energy
conserving
communication
techniques
become
increasingly important and are in fact subject to many
present research projects. DR Scheme uses static
clustering and minimum distance based CH selection. We
have used a two level hierarchy for inter cluster
communication. The beauty of our technique is the
formation of square and rectangular regions, which
divides the network field into small regions, as a result
the communication distance for intra cluster and inter
cluster reduces. However CR nodes associate with CH or
BS depending on the minimum distance. Characteristics
of achieving optimum number of CHs in each round and
hierarchical inter CHs communication of our technique
provided better results than its counterparts, in terms of
delay, energy consumption, packet loss and throughput.
However, large network area and greater number of nodes
decrease DR efficiency in terms of energy consumption.
ACKNOWLEGEMENT
I would like to place on record my deep sense of gratitude
to Er. Sarabjit Kaur for her generous guidance, help and
useful suggestions and supervision throughout the course
of research work.
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REFERENCES
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[4] B. Mamalis, D. Gavalas, C. Konstantopoulos and G. Pantziou
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