A hybrid localization model using node segmentation and improved particle swarm optimization with obstacle-awareness for wireless sensor networks

作者：

Highlights：

• Focusing the WSN localization precision with the obstruction.

• Proposing a novel anchor node segmenting technique to be used for WSN localization.

• Enhancing PSO adopt for the improvement of localization accuracy in WSN.

• Determining a new fitness function over hop counts for high estimation precision.

• Performing an intensive evaluation over a recent state of the art localization.

摘要

•Focusing the WSN localization precision with the obstruction.•Proposing a novel anchor node segmenting technique to be used for WSN localization.•Enhancing PSO adopt for the improvement of localization accuracy in WSN.•Determining a new fitness function over hop counts for high estimation precision.•Performing an intensive evaluation over a recent state of the art localization.

论文关键词：Localization,Node segmentation,Obstruction,Particle swarm optimization,Wireless Sensor Networks

论文评审过程：Received 4 July 2019, Revised 7 October 2019, Accepted 17 October 2019, Available online 30 October 2019, Version of Record 7 November 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.113044