Open AccessEnergy Efficient WSN Clustering Using Cuckoo Search
Author(s) -
Devershi Pallavi Bhatt,
Yogesh Kumar Sharma,
Anand Sharma
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1099/1/012048
Subject(s) - wireless sensor network , cluster analysis , computer science , cuckoo search , protocol (science) , task (project management) , cuckoo , energy (signal processing) , range (aeronautics) , energy conservation , computer network , distributed computing , real time computing , engineering , artificial intelligence , machine learning , medicine , statistics , alternative medicine , mathematics , electrical engineering , systems engineering , pathology , particle swarm optimization , aerospace engineering , zoology , biology
A comprehensive range of applications exists for Wireless Sensor Networks (WSNs) have in today’s world. To name a few they are used in monitoring environmental parameters, condition of infrastructures, and related geophysical processes near to real-time, water quality monitoring, air pollution monitoring, etc. Wireless sensors can be placed in places that are difficult to human intervention for impossible to reach with a physical wired system. These WSNs, are low in power and computation so constructing an energy-effective data collecting protocol is a demanding issue. This is because all sensor nodes are usually provided with limited power sources. The development of an energy-efficient algorithm is the need of the hour as replacing the energy sources for the sensor nodes is a tedious task. Various clustering protocols have been proposed earlier but they suffer unbalanced energy problems and are not efficient enough to cater to the needs of these WSNs. To deal with this challenge, an improved algorithm using cuckoo-based search clustering protocol has been proposed in this research paper.