Study and improvement on coverage control algorithm in WSN

2010 ◽  
Vol 30 (6) ◽  
pp. 1459-1462
Author(s):  
Yang TAO ◽  
Xiao-ling ZENG ◽  
Wei LUO
2011 ◽  
Vol 30 (6) ◽  
pp. 1437-1440
Author(s):  
Ying-xun Zhu ◽  
Rong Wang ◽  
Xiao-xin Yi

2020 ◽  
Vol 309 ◽  
pp. 03003
Author(s):  
Jie Zhou ◽  
Mengying Xu ◽  
Yi Lu ◽  
Rui Yang

Wireless sensor network has many sensor nodes with characteristics of limited cost, collecting data, good fault tolerance and storage. It has been used in environmental monitoring, health care, military and commercial. Coverage control is a significant issue that needs to be solved in wireless sensor networks. In order to solve the problem of overlapping coverage for environmental monitoring and improve coverage rate, an improved immune fuzzy genetic algorithm (IIFGA) based on cluster head selection is proposed. the mathematical model is systematically described. In the experiments, ant colony optimization (ACO) and simulated annealing (SA) are given to compare the performance of IIFGA. The experiments show the proposed coverage control algorithm has a higher convergence speed and improve the coverage rate.


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