Open AccessReal-time Monitoring Mechanism of Underwater WSN
Author(s) -
Dongjiao Guo,
Liu Yan-ping,
Bo Qiu,
Guanjie Xiang,
Mengci Li
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1626/1/012014
Subject(s) - computer science , wireless sensor network , node (physics) , underwater , energy consumption , convolutional neural network , minification , real time computing , key (lock) , polynomial , sensor node , artificial neural network , energy (signal processing) , algorithm , data mining , artificial intelligence , key distribution in wireless sensor networks , computer network , engineering , mathematics , telecommunications , statistics , mathematical analysis , oceanography , wireless network , electrical engineering , computer security , structural engineering , wireless , programming language , geology
Sensor node energy is the key to the long life cycle of a sensor network. This paper considers the correlation of sensor nodes in continuous time on-chip data transfer, and compares the derivative-based prediction, polynomial regression, back propagation and convolutional neural networks prediction algorithms for data transfer and energy consumption minimization. Experimental results show that convolutional neural networks are the optimal control solution.