Node self-localization algorithm for wireless sensor networks based on modified particle swarm optimization

Node self-localization is an important issue in wireless sensor networks (WSN). To solve this problem, a node self-localization algorithm is proposed. A modified particle swarm optimization (PSO) is introduced to find out the location of unknown nodes. It confirms the variation of particle to ensure...

Full description

Saved in:
Bibliographic Details
Published inThe 27th Chinese Control and Decision Conference (2015 CCDC) pp. 5968 - 5971
Main Authors Liu Zhi-kun, Liu Zhong
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2015
Subjects
Anchor Node
Classification algorithms
Convergence
Distance measurement
Node Self-localization
Particle swarm optimization
Robustness
Simulation
Wireless sensor networks
Online AccessGet full text

Cover

More Information
Summary:Node self-localization is an important issue in wireless sensor networks (WSN). To solve this problem, a node self-localization algorithm is proposed. A modified particle swarm optimization (PSO) is introduced to find out the location of unknown nodes. It confirms the variation of particle to ensure the steady convergence of the algorithm to global optimal solution. The simulation results show that the proposed algorithm can search global optimal solution faster than traditional PSO. Comparing with the least square (LS) method which is widely used in the field of node self-localization, the new algorithm has better robustness. The precision of localization is greatly advanced and less anchor nodes are needed.
ISSN:1948-9439
DOI:10.1109/CCDC.2015.7161879