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.
Original language | English (US) |
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Article number | 5740866 |
Pages (from-to) | 1943-1951 |
Number of pages | 9 |
Journal | IEEE Transactions on Parallel and Distributed Systems |
Volume | 22 |
Issue number | 11 |
DOIs | |
State | Published - 2011 |
Bibliographical note
Funding Information:This research was partially supported by the US National Science Foundation (NSF) grants CNS-0626609, CNS-0626614, and CRI-0708344.
Keywords
- RSD.
- Wireless sensor networks
- localization
- neighborhood sensing
- range free
- signature distance