Improved Deep Convolutional Neural Network based Malicious Node Detection and Energy-Efficient Data Transmission in Wireless Sensor Networks

2021 ◽  
pp. 1-1
Author(s):  
Mohit Kumar ◽  
Priya Mukherjee ◽  
Kavita Verma ◽  
Sahil Verma ◽  
Danda B Rawat
Keyword(s):  
Neural Network ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Convolutional Neural Network ◽  
Data Transmission ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Malicious Node ◽  
Efficient Data ◽  
Malicious Node Detection

An energy efficient data transmission approach for low-duty-cycle wireless sensor networks

2019 ◽  
Vol 13 (1) ◽  
pp. 255-268
Author(s):  
Jian Wu ◽  
Zhigang Chen ◽  
Jia Wu ◽  
Xiao Liu ◽  
Genghua Yu ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Duty Cycle ◽  
Data Transmission ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Low Duty Cycle ◽  
Efficient Data

scholarly journals An Energy-efficient Data Transmission Scheme in Underwater Wireless Sensor Networks

2016 ◽  
Vol 6 (2) ◽  
pp. 931-936 ◽  
Author(s):  
Y. Emami ◽  
R. Javidan
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Transmission ◽  
Energy Efficient ◽  
Bloom Filters ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Transmission Scheme ◽  
Efficient Data

Energy is a precious resource in underwater wireless sensor networks (UWSNs). In these networks, the number of data transmissions between sensor nodes dominates energy consumption. Complex signal processing techniques also increase energy consumption. In this paper an energy-efficient data transmission scheme based on bloom filters is proposed. Extensive simulation is carried out to demonstrate the effectiveness of the proposed method. Simulation results indicate that the proposed scheme outperforms the primary technique in terms of energy efficiency, lifetime, load and loss rate. The results of this research suggest that exploiting bloom filters is a viable solution for reducing the number of transmissions in UWSNs.

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