ETOC: Obtaining robustness in component-based localization

Accurate localization is crucial for wireless ad-hoc and sensor networks. Among the localization schemes, component-based approaches specialize in localization performance, which can properly conquer network sparseness and anchor sparseness. However, such design is sensitive to measurement errors. E...

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Vydáno v:The 18th IEEE International Conference on Network Protocols s. 62 - 71
Hlavní autoři: Xiaoping Wang, Yunhao Liu, Zheng Yang, Junliang Liu, Jun Luo
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.10.2010
Témata:
Ad hoc networks
Algorithm design and analysis
component-based
Coordinate measuring machines
Distance measurement
localization
location ambiguity
Measurement errors
Noise measurement
robust localization
Robustness
structural error tolerance
ISBN:1424486440, 9781424486441
ISSN:1092-1648
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Shrnutí:Accurate localization is crucial for wireless ad-hoc and sensor networks. Among the localization schemes, component-based approaches specialize in localization performance, which 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.
ISBN:1424486440
9781424486441
ISSN:1092-1648
DOI:10.1109/ICNP.2010.5762755