Comparative performance and energy consumption analysis of different AES implementations on a wireless sensor network node

2011 ◽  
Vol 10 (4) ◽  
pp. 192 ◽  
Author(s):  
Fan Zhang ◽  
Reiner Dojen ◽  
Tom Coffey
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Network Node ◽  
Comparative Performance ◽  
Energy Consumption Analysis

Research on Energy-Saving Technology of Wireless Sensor Network

2014 ◽  
Vol 513-517 ◽  
pp. 2257-2260
Author(s):  
Shao Feng Lin ◽  
Zhen Gui Zhang ◽  
Shu Gen Wang ◽  
Yao Zhou
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Energy Conservation ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Network Node ◽  
Signal Isolation ◽  
Compression Coding ◽  
Hardware Circuit ◽  
Conservation Design

As the wireless sensor network node battery is limited and changing battery is difficult, we did research on feasible energy conservation design technology. Paper analyzed energy consumption and the proportion of network node in work station of dormancy, data dealing, and communication and so on. Hardware circuit was promoted through power partition, signal isolation and low energy consumption chip application. Software program was optimized through state machine combined with differential compression coding. Then the purpose of extending network life can be reached. The experiment result shows that the energy conservation design can reduce the energy consumption greatly and extend the network life 2~3 times.

Node Deployment Algorithm Based on Perception Model of Wireless Sensor Network

2015 ◽  
Vol 9 (3) ◽  
pp. 210-215 ◽  
Author(s):  
Hengchang Jing ◽  
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Network Node ◽  
Coverage Problem ◽  
Node Deployment ◽  
Perception Model ◽  
Simulation Results

With the aim of solving the coverage problem of a wireless sensor network, a node deployment algorithm for the wireless sensor network, one based on a perception model, is designed in this work. The simulation results show that this algorithm can effectively deploy the wireless sensor network node, improve the network’s coverage, reduce the energy consumption of the network node, and help the network to function longer.

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