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Soft Computing

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18.06.2020 | Methodologies and Application

Weight convergence analysis of DV-hop localization algorithm with GA

verfasst von: Xingjuan Cai, Penghong Wang, Zhihua Cui, Wensheng Zhang, Jinjun Chen

Erschienen in: Soft Computing | Ausgabe 23/2020

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Abstract

The distance vector-hop (DV-hop) is a typical localization algorithm. It estimates sensor nodes location through detecting the hop count between nodes. To enhance the positional precision, the weight is used to estimate position, and the conventional wisdom is that the more hop counts are, the smaller value of weight will be. However, there has been no clear mathematical model among positioning error, hop count, and weight. This paper constructs a mathematical model between the weights and hops and analyzes the convergence of this model. Finally, the genetic algorithm is used to solve this mathematical weighted DV-hop (MW-GADV-hop) positioning model, the simulation results illustrate that the model construction is logical, and the positioning error of the model converges to 1/4R.

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Titel: Weight convergence analysis of DV-hop localization algorithm with GA
verfasst von: Xingjuan Cai
Penghong Wang
Zhihua Cui
Wensheng Zhang
Jinjun Chen
Publikationsdatum: 18.06.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 23/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-020-05088-z

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