RSD: A metric for achieving range-free localization beyond connectivity

Ziguo Zhong, Tian He

Research output: Contribution to journalArticlepeer-review

67 Scopus citations


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 languageEnglish (US)
Article number5740866
Pages (from-to)1943-1951
Number of pages9
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number11
StatePublished - 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.


  • RSD.
  • Wireless sensor networks
  • localization
  • neighborhood sensing
  • range free
  • signature distance

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