Distributed fermat-point location estimation for wireless sensor network applications

Jiann Liang Chen, Ming Chiao Chen, Tsui Lien Chiang, Yao Chung Chang, Frank Y. Shih

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


This paper presents a distributed fermat-point range estimation strategy, which is important in the moving sensor localization applications. The fermat-point is defined as a point which minimizes the sum of distances from three sensors inside a triangle. This point is indeed at the triangle's center of gravity. We solve the problems of large errors and poor performance in the bounding box algorithm. We obtain two results by performance analysis for a deployed environment with 200 sensor nodes. First, when the number of sensor nodes is below 150, the mean error decreases rapidly as the node density increases, and when the number of sensor nodes exceeds 170, the mean error stays below 1%. Second, when the number of beacon nodes is below 60, the normal nodes do not have sufficient number of accurate beacon nodes to help them estimate their locations. However, when the number of beacon nodes exceeds 60, the mean error changes slightly. Simulation results indicated that the proposed algorithm for sensor position estimation is more accurate than existing algorithms and improves on existing bounding box strategies.

Original languageEnglish (US)
Title of host publication2007 IEEE Sarnoff Symposium, SARNOFF
StatePublished - 2007
EventIEEE Sarnoff Symposium, SARNOFF 2007 - Princeton, NJ, United States
Duration: Apr 30 2007May 2 2007

Publication series

Name2007 IEEE Sarnoff Symposium, SARNOFF


OtherIEEE Sarnoff Symposium, SARNOFF 2007
Country/TerritoryUnited States
CityPrinceton, NJ

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Electrical and Electronic Engineering
  • Communication


  • Bounding box algorithm
  • Distributed Fermat-Point Location Estimation (DFPLE)
  • Range estimation
  • Wireless sensor network


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