scholarly journals Data compression algorithms for sensor networks with periodic transmission schemes

2022 ◽  
Vol 355 ◽  
pp. 03003
Author(s):  
Jianxin Chen ◽  
Pengcheng Wang ◽  
Xinzhuo Ren ◽  
Haojie Meng ◽  
Yinfei Xu ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Data Compression ◽  
Original Data ◽  
Transmission Model ◽  
Complex Environment ◽  
Compression Method ◽  
Theoretical Derivation ◽  
Memory Space ◽  
Change Trend ◽  
Periodic Transmission

The operating state of switch cabinet is significant for the reliability of the whole power system, collecting and monitoring its data through the wireless sensor network is an effective method to avoid accidents. This paper proposes a data compression method based on periodic transmission model under the condition of limited energy consumption and memory space resources in the complex environment of switch cabinet sensor networks. Then, the proposed method is rigorously and intuitively shown by theoretical derivation and algorithm flow chart. Finally, numerical simulations are carried out and compared with the original data. The comparisons of compression ratio and error results indicate that the improved algorithm has a better effect on the periodic sensing data with interference and can make sure the change trend of data by making certain timing sequence.

scholarly journals Robust Data Compression for Irregular Wireless Sensor Networks Using Logical Mapping

2013 ◽  
Vol 2013 ◽  
pp. 1-18 ◽  
Author(s):  
Thanh Dang ◽  
Nirupama Bulusu ◽  
Wu-chi Feng
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Compression ◽  
Spatial Data ◽  
Original Data ◽  
Wireless Sensor ◽  
Discrete Wavelet ◽  
Data Correlation ◽  
Real World Data ◽  
Logical Mapping

We propose RIDA, a novel robust information-driven data compression architecture for distributed wireless sensor networks. The key idea is to determine the data correlation among a group of sensors based on the data values to significantly improve compression performance rather than relying solely on spatial data correlation. A logical mapping approach assigns virtual indices to nodes based on the data content, which enables simple implementation of data transformation on resource-constrained nodes without any other information. We evaluate RIDA with both discrete cosine transform (DCT) and discrete wavelet transform (DWT) on publicly available real-world data sets. Our experiments show that 30% of energy and 80–95% of bandwidth can be saved for typical multihop data networks. Moreover, the original data can be retrieved after decompression with a low error of about 3%. In particular, for one state-of-the-art distributed data compression algorithm for sensor networks, we show that the compression ratio is doubled by using logical mapping while maintaining comparable mean square error. Furthermore, we also propose a mechanism to detect and classify missing or faulty nodes, showing accuracy and recall of 95% when half of the nodes in the network are missing or faulty.

scholarly journals Modified Chorological Coded Data Compression Methodology for Wireless Sensor Networks

2021 ◽  
Vol 1770 (1) ◽  
pp. 012026
Author(s):  
S. Jancy ◽  
Suji Helen ◽  
Mercy Paul Selven ◽  
A. Viji Amutha Mary ◽  
M.D Antopraveena ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Compression ◽  
Wireless Sensor
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