Research of an improved weighted centroid localization algorithm and anchor distribution

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Localization plays an important role in Wireless Sensor Networks. This paper proposed a weighted centroid localization algorithm based on received signal strength difference (RDWCL). RDWCL utilizes RSSI difference to calculate weight so as to improve localization precision and reduce the impact of anchor density and environment changing. Anchor distribution is also introduced and analyzed in this paper. Simulation and experiment results show that compared with Centroid and Weighted Centroid, RDWCL has better performance. When anchor nodes are randomly deployed, the accuracy has been improved by 13.5%. When anchor nodes are deployed as grid, the accuracy has been improved by 25.04%. When anchor nodes are deployed as equilateral triangle, the accuracy has been improved by 27.4%.

Original languageEnglish
Title of host publicationProceedings - 2010 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2010
Pages400-405
Number of pages6
DOIs
StatePublished - 2010
Event2nd International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2010 - Huangshan, China
Duration: 10 Oct 201012 Oct 2010

Publication series

NameProceedings - 2010 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2010

Conference

Conference2nd International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2010
Country/TerritoryChina
CityHuangshan
Period10/10/1012/10/10

Keywords

  • Anchor distribution
  • Localization accuracy
  • Localization algorithm
  • RSSI difference
  • Wireless sensor networks

Fingerprint

Dive into the research topics of 'Research of an improved weighted centroid localization algorithm and anchor distribution'. Together they form a unique fingerprint.

Cite this