Open AccessA coordinate compression algorithm based on centroid for wireless sensor networks
Author(s) -
Xiangli Liu,
Zan Li,
Hu Yi-Su
Publication year - 2013
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.62.070201
Subject(s) - centroid , computer science , inverse trigonometric functions , algorithm , data compression , compression (physics) , compression ratio , data compression ratio , nonlinear system , wireless sensor network , signal (programming language) , signal compression , computation , sampling (signal processing) , signal processing , image compression , artificial intelligence , mathematics , computer vision , digital signal processing , filter (signal processing) , engineering , materials science , computer network , composite material , image (mathematics) , image processing , mathematical analysis , quantum mechanics , programming language , internal combustion engine , physics , automotive engineering , computer hardware
Since communication is often constrainted and the computational resources are limited in wireless sensor networks, it is more important for local sensors to send in compressed data. In this paper, a nonlinear coordinate compression rule is constructed based on arctangent function. Beneficial from the nonlinear feature of arctangent function, near the centroid the compression ratio is low and apart from the centroid the compression ratio becomes higher and higher. The proposed algorithm is more suitable for the signal that has a useful high frequency near centroid. And the proposed algorithm has the following features: the sampling interval is not even; the compression can be done before sampling, which is similar to a compression sensing; it has low computation amount, is simple and easy to implement in a real system.