Robust Component-Based Localizationin Sparse Networks

Accurate localization is crucial for wireless ad-hoc and sensor networks. Among the localization schemes, component-based approaches specialize in localization performance. By grouping nodes into increasingly large rigid components, component-based localization algorithms can properly conquer networ...

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Bibliographic Details
Published in:IEEE transactions on parallel and distributed systems Vol. 25; no. 5; pp. 1317 - 1327
Main Authors: Wang, Xiaoping, Liu, Yunhao, Yang, Zheng, Lu, Kai, Luo, Jun
Format: Journal Article
Language:English
Published: New York IEEE 01.05.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithm design and analysis
Algorithms
Component-based localization
Design engineering
Distance measurement
Educational institutions
Errors
Localization
location ambiguity
Measurement errors
Networks
Noise measurement
Position (location)
Product design
Reflection
robust localization
Robustness
structural error tolerance
Transformations
Two dimensional
ISSN:1045-9219, 1558-2183
Online Access:Get full text
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Summary:Accurate localization is crucial for wireless ad-hoc and sensor networks. Among the localization schemes, component-based approaches specialize in localization performance. By grouping nodes into increasingly large rigid components, component-based localization algorithms can properly conquer network sparseness and anchor sparseness. However, such design is sensitive to measurement errors. Existing robust localization methods focus on eliminating the positioning error of a single node. Indeed, a single node has two dimensions of freedom in 2D space and only suffers from one type of transformation: translation. As a rigid 2D structure, a component suffers from three possible transformations: translation, rotation, and reflection. A high degree of freedom brings about complicated cases of error productions and difficulties on error controlling. This study is the first work addressing how to deal with ranging noises for component-based methods. By exploiting a set of robust patterns, we present an Error-TOlerant Component-based algorithm (ETOC) that not only inherits the high-performance characteristic of component-based methods, but also achieves robustness of the result. We evaluate ETOC through a real-world sensor network consisting of 120 TelosB motes as well as extensive large-scale simulations. Experiment results show that, comparing with the-state-of-the-art designs, ETOC can work properly in sparse networks and provide more accurate localization results.
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ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2013.85