A Gaussian error correction multi‐objective positioning model with NSGA‐II. (8th August 2019)

• Record Type: Journal Article
• Authors: Wang, Penghong; Huang, Jianrou; Cui, Zhihua; Xie, Liping; Chen, Jinjun
• Is Part Of: Concurrency and computation. Volume 32:Number 5(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-08-08
• Subjects: Gaussian error correction -- GGAII‐DVHop -- multi‐objective DVHop model -- wireless sensor networks; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.5464
• Languages: English
• ISSNs: 1532-0626

Abstract

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.