Open AccessEnergy Efficient Heterogeneous WNS Clustering Using Machine Learning
Author(s) -
Kamini Maheshwar,
S. Veenadhari,
Almelu
Publication year - 2021
Publication title -
smart moves journal ijoscience
Language(s) - English
Resource type - Journals
ISSN - 2582-4600
DOI - 10.24113/ijoscience.v7i6.391
Subject(s) - wireless sensor network , cluster analysis , computer science , key distribution in wireless sensor networks , rendering (computer graphics) , mobile wireless sensor network , computer network , energy conservation , wireless , wireless network , telecommunications , engineering , artificial intelligence , electrical engineering
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