Estimation of sensor-network topology from time-series sensor data using ant colony optimization method

Kensuke Takahashi, Toshiharu Sugawara

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

2 Citations (Scopus)

Abstract

We propose a method for estimating sensor network topology from only with time-series sensor data and without prior knowledge about the locations of sensors. The proposed method is based on ant colony optimization (ACO) but is further improved, compared with previous work[s], to construct a more accurate topology through an examination of the reliability of the acquired sensor data for the adjacency estimation. This reliability value is used to control the amount of pheromones deposited. We evaluate our method using actual sensor data and show that it can estimate adjacencies, in which the error rate is approximately 87% less than that of the previous method.

Original languageEnglish
Title of host publication2008 IEEE Swarm Intelligence Symposium, SIS 2008
DOIs
Publication statusPublished - 2008 Dec 22
Event2008 IEEE Swarm Intelligence Symposium, SIS 2008 - St. Louis, MO, United States
Duration: 2008 Sep 212008 Sep 23

Publication series

Name2008 IEEE Swarm Intelligence Symposium, SIS 2008

Conference

Conference2008 IEEE Swarm Intelligence Symposium, SIS 2008
CountryUnited States
CitySt. Louis, MO
Period08/9/2108/9/23

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Electrical and Electronic Engineering

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