Wireless sensor networks (WSNs) are very popular in the real world applications such as battlefield monitoring;
estimating traffic flows, monitor the natural phenomena, environmental changes etc. The limited size of battery is the main
drawback of WSN. When the battery is exhausted then the several nodes die and of no use. To remove such type of failure in the
network, many researches are carried out in the energy saving scheme. Clustering is the main issue in the wireless sensor
network because it enhances the network lifetime. Many optimization techniques applied while selecting the cluster head
selection. Here, we present survey on the neural network based clustering concept which enhances the network lifetime of the
network.
Published In:IJCSN Journal Volume 6, Issue 1
Date of Publication : February 2017
Pages : 49-54
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Inderjeet Singh : Research Scholar, CTIEMT Shahpur, Jalandhar, Punjab, India.
Pooja : Assistant Professor, CTIEMT Shahpur, Jalandhar Punjab, India.
Varsha : Assistant Professor, CTIEMT Shahpur, Jalandhar Punjab, India.
This paper concluded a survey of the most important
application of neural network. The main purpose of the
study is to select the cluster head which aggregates the data
and send it to the sink by the use of neural network which
enhances the network lifetime. The learning factor is the
important factor in neural network. The neural network is
the intelligent tool which deals with the problem associated
in sensing and processing data at the end of sensor node. The
most important application of NN is data prediction, data
fusion, path discovery in routing and nodes clustering which
lead to less communication cost in WSN. In the future work,
more concentration is on network topologies and on the
energy conservation.
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