Lifting Wavelet Compression Based Data Aggregation in Big Data Wireless Sensor Networks

Author(s):  
Ledan Cheng ◽  
Songtao Guo ◽  
Ying Wang ◽  
Yuanyuan Yang
2013 ◽  
Vol 442 ◽  
pp. 526-531
Author(s):  
Xian Li Li ◽  
Jia Wei Zhang ◽  
Hai Tao Zhang

Considering the limited resources and data transmission redundancy of wireless sensor networks, this paper proposes a distributed data aggregation algorithm based on lifting wavelet transform (DDAA-LWT), and carries out the rational design. The algorithm distributes the computing quantity which the lifting wavelet transform requires to all network nodes, eliminates the additional computing and wireless transmission, reduces the information redundancy of network, greatly prolongs the lifecycle of wireless sensor networks. Simulation results demonstrate that the distributed data aggregation algorithm based on lifting wavelet transform (DDAA-LWT) can effectively aggregate the original sensed data and decrease the energy consumption, it significantly outperforms the data aggregation algorithm based on traditional wavelet transform (DAA-WT).


IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 20558-20571 ◽  
Author(s):  
Sabrina Boubiche ◽  
Djallel Eddine Boubiche ◽  
Azeddine Bilami ◽  
Homero Toral-Cruz

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