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ABSTRACT
Data gathering is a common but critical operation in many
applications of wireless sensor networks. Innovative
techniques that improve energy efficiency to prolong the
network lifetime are highly required. Clustering is an
effective topology control approach in wireless sensor
networks, which can increase network scalability and
lifetime. Clustering sensors into groups, so that sensors
communicate information only to cluster heads and then the
cluster heads communicate the aggregated information to
the processing centre, may save energy. In this paper, we
simulate a distributed, randomized clustering algorithm to
organize the sensors in a wireless sensor network into
clusters in MATLAB. EEHCA [1] (an Energy Efficient
Hierarchical Clustering Algorithm for Wireless Sensor
Networks) achieves a good performance in terms of
lifetime by minimizing energy consumption for
communication and balancing the energy loads among all
the nodes.
INTRODUCTION
Due to the increase in the development of wireless
communication and MEMS technology the use of sensor
networks has become more demanding and useful [3].
These sensor networks are small in size and are not
expensive, as they have their own limited power supply
from onboard 1 joule battery .The functions of these are
sensing, signal processing and wireless communication.
Since the sensors have limited power supply, therefore to make up for the data rate and transmission range they send
data to the nearest sensors and use multi hop
communication to reduce energy consumption. The sensors
in a given area collect information and transmit it to the
sink or one more sensor which acts as the centre .To keep
the cost minimum we adopt the cluster method of
communication in wireless sensor networks, since the cost
of transmitting a bit is higher than data
Processing one important application of WSN is data
gathering, which uses techniques such as data aggregation
and clustering hierarchical mechanism. The former helps in
reducing redundancy and the overall communication load
on sensors whereas the latter help in increasing the
scalability and reducing data latency.
II. THEOREY
Wireless sensor network is a network which contains many
small spatially distributed sensing devices called sensors
which is shown in figure 1. These devices help in gathering
information like temperature, pressure, humidity, military
applications, target tracking etc. Basic features of sensor
networks are self-organizing capabilities, dynamic network
topology, limited power, node/communication failures, and
mobility of nodes, short-range broadcast communication
and multi-hop routing, and large scale of deployment.
The strength of wireless sensor network lies in their
flexibility and scalability. The capability of self-organize
and wireless communication enables them to be deployed
in remote or hazardous location without the need of any
existing infrastructure. Through multi-hop communication
a sensor node can communicate to a far away node in the
network. This allows the addition of sensor nodes in the
network to expand the monitored area and hence proves its
scalability & flexibility property
The amount of energy used up in transferring a bit of
data is equal to many operations in sensor networks, also in
an area which has a large number of sensors; transferring of
data to a nearby sensor with same information will cause
data redundancy.
Therefore we use the method of forming clusters. This
way we can reduce data redundancy. It also helps in
compressing data so that only compact data is sent, hence
reducing both global and local traffic This process of
grouping of sensor nodes in a densely deployed large-scale
sensor network is known as clustering. With the help of its unique feature it can be used in various application such as
pattern recognition, compression in images and video
database.
There are three types of cluster’s (CH) cluster heads,
(GN) gateway node and (NN) normal node [5]. Each
cluster has a cluster head which co-ordinates and controls
the data that the normal node in its cluster wants to
transmit. There is no direct communication between two
normal nodes. They can only communicate through their
respective cluster heads.