Title :
Node self-localization algorithm for wireless sensor networks based on modified particle swarm optimization
Author :
Liu Zhi-kun ; Liu Zhong
Author_Institution :
Electron. Eng. Coll., Naval Univ. of Eng., Wuhan, China
Abstract :
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.
Keywords :
least squares approximations; particle swarm optimisation; wireless sensor networks; LS method; WSN; least square method; modified particle swarm optimization; node self-localization algorithm; particle variation; wireless sensor networks; Classification algorithms; Convergence; Distance measurement; Particle swarm optimization; Robustness; Simulation; Wireless sensor networks; Anchor Node; Node Self-localization; Particle Swarm Optimization; Wireless Sensor Networks;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7161879