Abstract

Many applications of wireless sensor networks (WSNs) require location information of the randomly deployed nodes. a common solution to the localization problem is to deploy a few special beacon nodes having location awareness, which help the ordinary nodes to localize. in this approach, non-beacon nodes estimate their locations using noisy distance measurements from three or more non-collinear beacons they can receive signals from. in this paper, the ranging-Based localization task is formulated as a multidimensional optimization problem, and addressed using bio-inspired algorithms, exploiting their quick convergence to quality solutions. an investigation on distributed iterative localization is presented in this paper. Here, the nodes that get localized in an iteration act as references for remaining nodes to localize. the problem has been addressed using particle swarm optimization (PSO) and bacterial foraging algorithm (BFA). a comparison of the performances of PSO and BFA in terms of the number of nodes localized, localization accuracy and computation time is presented. ©2009 IEEE.

Department(s)

Electrical and Computer Engineering

Second Department

Computer Science

Keywords and Phrases

Bacterial foraging algorithm; Localization; Particle swarm optimization; Wireless sensor networks

International Standard Book Number (ISBN)

978-142442794-9

International Standard Serial Number (ISSN)

1062-922X

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

01 Dec 2009

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