A Honeycomb Shape Localization Algorithm Based on Levy-PSO

DOI

10.2991/mmetss-16.2017.113How to use a DOI?

Keywords

WSNs,particle swarm optimization(PSO),honeycomb,the least squares fitting,Levy flight mechanism

Abstract

The positioning technology is of vital importance in Wireless Sensor Networks (WSNs), and its accuracy based on particle swarm optimization (PSO) is low. Therefore, this paper considers the problem of low positioning accuracy and slow speed of convergence by proposing a honeycomb shape localization algorithm based on Levy-PSO. First, the communication distance and ranging error analysis shows that there is an optimal length can improve localization accuracy. Then, the localization area is divided into several honeycomb sub-regions with the optimal length. The unknown node communicates with at least six beacon nodes to ensure the reliability of the results. And these honeycomb sub-regions develop their environmental parameters which are calculated from the least squares fitting method. Last, we develop the PSO algorithm with Levy flight mechanism. The simulation results are show the way this algorithm could improve the positioning accuracy in order to have better stability,

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Dongyao Zou
AU  - Biwei Liu
AU  - Chen Li
PY  - 2017/02
DA  - 2017/02
TI  - A Honeycomb Shape Localization Algorithm Based on Levy-PSO
BT  - Proceedings of the 2016 International Conference on Modern Management, Education Technology, and Social Science (MMETSS 2016)
PB  - Atlantis Press
SP  - 166
EP  - 172
SN  - 2352-5398
UR  - https://doi.org/10.2991/mmetss-16.2017.113
DO  - 10.2991/mmetss-16.2017.113
ID  - Zou2017/02
ER  -