Energy Efficient Heterogeneous WNS Clustering Using Machine Learning

Authors

  • Kamini Maheshwar
  • Dr. S. Veenadhari
  • Mr Almelu

DOI:

https://doi.org/10.24113/ijoscience.v7i6.391

Keywords:

HWSN, Clustering, Energy Efficient.

Abstract

Heterogeneous wireless sensor network (HWSN) fulfills the requirements of researchers in the design of real-life application to resolve the issues of unattended problem. Wireless sensor networks are used in diverse areas such as battlefields, security, hospitals, universities, etc. It has been used in our everyday lives. Its development is rising day by day. Wireless sensor network includes hundreds to thousands of sensor nodes which aid in gathering various information like temperature, sound, location, etc. Recharging or modifying sensor nodes which might have limited battery power is usually difficult. Therefore, energy conservation is a crucial concern in sustaining the network. Clustering the networks is definitely one of the most common solutions for rendering WSNs energy. In this paper,   review and compare different energy-efficient clustering protocols for WSNs

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Author Biographies

Kamini Maheshwar

PhD Scholar

Computer Science & Engineering,

Rabindranath Tagore University

Bhopal, India

 

Dr. S. Veenadhari

Associate Professor

Computer Science & Engineering

Rabindranath Tagore University

Bhopal, India

 

Mr Almelu

PhD Scholar

Computer Science & Engineering, Rabindranath Tagore University

Bhopal, India

 

References

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Anurag Chatap, Sumedha Sirsikar,” Review On Various Routing Protocols For Heterogeneous Wireless SensorNetwork,”IEEE, 2017.

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Published

06/24/2021

How to Cite

Maheshwar, K. ., Veenadhari, D. S. ., & Almelu, M. (2021). Energy Efficient Heterogeneous WNS Clustering Using Machine Learning. SMART MOVES JOURNAL IJOSCIENCE, 7(6), 24–29. https://doi.org/10.24113/ijoscience.v7i6.391

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Articles