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A Gaussian error correction multi‐objective positioning model with NSGA‐II
Author(s) -
Wang Penghong,
Huang Jianrou,
Cui Zhihua,
Xie Liping,
Chen Jinjun
Publication year - 2019
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5464
Subject(s) - robustness (evolution) , gaussian , computer science , algorithm , sorting , wireless sensor network , range (aeronautics) , gaussian network model , distance measurement , position (finance) , artificial intelligence , engineering , physics , quantum mechanics , computer network , biochemistry , chemistry , finance , economics , gene , aerospace engineering
Summary Distance vector‐hop (DVHop), as a range‐independent positioning algorithm, is a significant positioning method in wireless sensor networks (WSNs). It is composed of three parts, including connectivity detection, distance estimation, and position estimation. However, this simple positioning method results in a larger positioning error. Therefore, to enhance the positioning precision, this paper investigates the characteristic of error distribution between the estimated and real distance in the DVHop algorithm and reveals that the error is subjecting to the Gaussian distribution, N∼(0,1/3CR). Furthermore, to improve positioning accuracy, we propose a Gaussian error correction multi‐objective positioning model with non‐dominated sorting (NSGA‐II), which named GGAII‐DVHop. Finally, this model is tested on three complex network topologies, and the results demonstrate that it is significantly superior to other four algorithms in both positioning precision and robustness.