Clustering algorithm based on nature-inspired approach for energy optimization in heterogeneous wireless sensor network

2021 ◽  
Vol 104 ◽  
pp. 107171
Author(s):  
Israel Edem Agbehadji ◽  
Richard C. Millham ◽  
Abdultaofeek Abayomi ◽  
Jason J. Jung ◽  
Simon James Fong ◽  
...  
2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
C. Vimalarani ◽  
R. Subramanian ◽  
S. N. Sivanandam

Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.


2019 ◽  
Vol 4 (5) ◽  
pp. 306-313
Author(s):  
Hamid Ali Abed AL-Asadi ◽  
Abdulhadi Alhassani ◽  
Nor Azura Ahmed Hambali ◽  
Mustafa Abdulazeez AlSibahee ◽  
Saif Ali Alwazzan ◽  
...  

2013 ◽  
Vol 32 (4) ◽  
pp. 920-923
Author(s):  
Ding DING ◽  
Fang-ai LIU ◽  
Qian-qian LI ◽  
Guang-xu YANG

2013 ◽  
Vol 33 (12) ◽  
pp. 3410-3414 ◽  
Author(s):  
Congcong MIAO ◽  
Qingkui CHEN ◽  
Jianwei CAO ◽  
Gang ZHANG

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