LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Optimized localization of target nodes using single mobile anchor node in wireless sensor network

Photo from wikipedia

Abstract In Wireless Sensor Networks (WSNs), main challenges which restrict the performance are data computation, lifetime, routing, task scheduling, security, organization and localization. Recently, numerous Computational Intelligence (CI) based potential… Click to show full abstract

Abstract In Wireless Sensor Networks (WSNs), main challenges which restrict the performance are data computation, lifetime, routing, task scheduling, security, organization and localization. Recently, numerous Computational Intelligence (CI) based potential solutions for above mentioned challenges have been proposed to fulfill the desired level of performance in WSNs. Use of CI gives autonomous and strong solutions to ascertain precise node location (2D/3D) with least hardware necessity (position finding device, i.e., GPS empowered gadget). Localization of target nodes in static scenario can be done more precisely. However, in case of mobility, determining accurate position of each node in network is a challenging problem. In this paper, a novel idea of localizing target nodes with moving single anchor node is proposed using CI based application of Particle Swarm Optimization (PSO) and H-Best Particle Swarm Optimization (HPSO). The moving anchor node is following the Hilbert trajectory. Proposed algorithms are actualized for range-based, distributed, non-collaborative and isotropic WSNs. Only single moving anchor node is used as a reference node to localize the target nodes in the entire network. In proposed algorithms, problem of Line of Sight (LoS) is minimized due to projection of virtual anchor nodes.

Keywords: node; localization; target nodes; anchor node

Journal Title: AEU - International Journal of Electronics and Communications
Year Published: 2018

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.