Estimation of sensor network topology using ant colony optimization

Kensuke Takahashi*, Satoshi Kurihara, Toshio Hirotsu, Toshiharu Sugawara

*Corresponding author for this work

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

4 Citations (Scopus)


We propose a method for estimating sensor network topology using only time-series sensor data without prior knowledge of the locations of sensors. Along with the advances in computer equipment and sensor devices, various sensor network applications have been proposed. Topology information is often mandatory for predicting and assisting human activities in these systems. However, it is not easy to configure and maintain this information for applications in which many sensors are used. The proposed method estimates the topology accurately and efficiently using ant colony optimization (ACO). Our basic premise is to integrate ACO with the reliability of acquired sensor data for the adjacency to construct the accurate topology. We evaluated our method using actual sensor data and showed that it is superior to previous methods.

Original languageEnglish
Title of host publicationAdaptive and Natural Computing Algorithms - 9th International Conference, ICANNGA 2009, Revised Selected Papers
Number of pages10
Publication statusPublished - 2009
Event9th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2009 - Kuopio, Finland
Duration: 2009 Apr 232009 Apr 25

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5495 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference9th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2009

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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