International Journal of Scientific Research and Engineering Development-– Volume 3 Issue 2, Mar-Apr 2020
Available at www.ijsred.com
ISSN : 2581-7175 ©IJSRED:All Rights are Reserved Page 929
Energy Harvesting Clustering Methodology for Lifetime
Enhancement of Wireless Sensor Networks
Nibedita Priyadarshini Mohapatra*, Rajesh Kumar Patjoshi**
*(Department of Computer Science Engineering, National Institute of Science &Technology,Berhampur,India
** (Department of Electronics and Comm. Engg., National Institute of Science &Technology,Berhampur,India
Email: rajeshpatjoshi1@gmail.com)
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Abstract:
In the modern era, wireless sensor network (WSN) has one of the new horizons among the research
community. A WSN provides largest range of network in most of the application fields and it can be
deployed anywhere. WSN has low cost, low power sensor nodes, can be deployed in large numbers and
also used in hazardous environment. However, the sensor nodes in WSN do not have longer lifetime and
always energy budget plays vital role in the context of wireless sensor network. Therefore, this paper
focuses on the issues related to network stability and complexity of the network. Moreover, maintenance
of fault tolerance ability and minimization of data losses through improved network stability are
accomplished in this work. As a result, the field lifetime of sensor nodes should be enhanced to encounter
the aforesaid challenges through sensor node. Therefore, the present study proposes the energy harvesting
clustering model for increasing lifetime of the network node via application of energy towards the sensor
node through energy harvesting concept and clustering technique. The proposed model is validated
through MATLAB and a comparative assessment is performed with an existing model.
Keywords —Clustering, Degradation, Energy harvesting, Field Lifetime, Wireless Sensor Network
(WSN).
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I. INTRODUCTION
Energy harvesting in wireless sensor networks
(WSN) [1, 2] is one of the essential concerns to be
considered, as energy in the sensor node (SN)
decreases when it is utilized in wide spectrum
applications. Indeed, wireless SN, is being
frequently utilized for outdoor applications [3] in
almost all fields, ranging from environment
monitoring to battlefield scenario and in computing
as well as communication platforms. Additionally,
WSN sets a new level for monitoring environments
and concerned to remote geographical area where
human intervention is not possible [4]. Every sensor
node in WSNs consists of four basic units namely
sensor unit, transceiver unit, processor unit and
power unit [5]. Fig.1 shows the different units of a
typical sensor node, which is consisting of analog to
digital converter (ADC), processor sensor,
transceiver and power unit. However, the
performance of the sensor unit is to sense the
specific environmental conditions such as
temperature, pressure level, humidity level and other
useful information [6, 7]. This information is
converted to digital signal for communication
purpose through an ADC.
Fig. 1 Different units of a typical sensor node
RESEARCH ARTICLE OPEN ACCESS