Slip surface localization in wireless sensor networks for landslide prediction

Terzis, Andreas; Anandarajah, A.; Moore, Kevin L.; Wang, I-Jeng

doi:10.1145/1127777.1127797

Cited by 64 publications

(39 citation statements)

References 13 publications

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“…W IRELESS sensor networks (WSN) have been proposed for many location-sensitive applications [1], such as battlefield monitoring [2], environment surveillance [3], object tracking [4], etc. In addition, many routing and management protocols [5], [6] proposed for such networks are built on the assumption that geographic parameters of sensor nodes are available.…”

Section: Introductionmentioning

confidence: 99%

RSD: A Metric for Achieving Range-Free Localization beyond Connectivity

Zhong

2011

IEEE Trans. Parallel Distrib. Syst.

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Abstract-Wireless sensor networks have been considered as a promising tool for many location-dependent applications. In such deployments, the requirement of low system cost prohibits many range-based methods for sensor node localization; on the other hand, range-free approaches depending only on radio connectivity may underutilize the proximity information embedded in neighborhood sensing. In response to these limitations, this paper introduces a proximity metric called RSD to capture the distance relationships among 1-hop neighboring nodes in a range-free manner. With little overhead, RSD can be conveniently applied as a transparent supporting layer for state-of-the-art connectivity-based localization solutions to achieve better accuracy. We implemented RSD with three well-known algorithms and evaluated using two outdoor test beds: an 850-foot-long linear network with 54 MICAz motes, and a regular 2D network covering an area of 10,000 square feet with 49 motes. Results show that our design helps eliminate estimation ambiguity with a subhop resolution, and reduces localization errors by as much as 35 percent. In addition, simulations confirm its effectiveness for large-scale networks and reveal an interesting feature of robustness under unevenly distributed radio path loss.

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Section: Introductionmentioning

confidence: 99%

RSD: A Metric for Achieving Range-Free Localization beyond Connectivity

Zhong

2011

IEEE Trans. Parallel Distrib. Syst.

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“…Wireless sensor networks (WSN) have been considered as a promising tool for many location-dependent applications [1,2], e.g., battlefield surveillance [3], environment data collection [4], event or human localization [5,6]. In addition, some of the routing protocols [7,8] and network management mechanisms proposed for such networks are built on the assumption that geographic parameters of each sensor node are available.…”

Section: Introductionmentioning

confidence: 99%

Achieving range-free localization beyond connectivity

Zhong

2009

Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems

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Wireless sensor networks have been proposed for many location-dependent applications. In such applications, the requirement of low system cost prohibits many range-based methods for sensor node localization; on the other hand, range-free localization depending only on connectivity may underutilize the proximity information embedded in neighborhood sensing. In response to the above limitations, this paper presents a range-free approach to capturing a relative distance between 1-hop neighboring nodes from their neighborhood orderings that serve as unique high-dimensional location signatures for nodes in the network. With little overhead, the proposed design can be conveniently applied as a transparent supporting layer for many state-of-the-art connectivity-based localization solutions to achieve better positioning accuracy. We implemented our design with three well-known localization algorithms and tested it in two types of outdoor test-bed experiments: an 850-foot-long linear network with 54 MICAz motes, and a regular 2D network covering an area of 10000 square feet with 49 motes. Results show that our design helps eliminate estimation ambiguity with sub-hop resolution, and reduces localization errors by as much as 35%. In addition, extensive simulations reveal an interesting feature of robustness for our design under unevenly distributed radio propagation path loss, and confirm its effectiveness for large-scale networks.

show abstract

“…Localization is a fundamental issue of wireless sensor networks and it's vital to many applications, such as battlefield surveillance [1], environmental monitoring [2], target tracking [3]. Furthermore, many routing and management protocols, proposed such a network is based on the assumption that the geographic parameters of the sensor nodes are available.…”

Section: Introductionmentioning

confidence: 99%