Estimation of sensor network topology using ant colony optimization

Kensuke Takahashi, Satoshi Kurihara, Toshio Hirotsu, Toshiharu Sugawara

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルAdaptive and Natural Computing Algorithms - 9th International Conference, ICANNGA 2009, Revised Selected Papers
ページ263-272
ページ数10
DOI
出版ステータスPublished - 2009
外部発表はい
イベント9th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2009 - Kuopio, Finland
継続期間: 2009 4 232009 4 25

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
5495 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other9th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2009
国/地域Finland
CityKuopio
Period09/4/2309/4/25

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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