Pheromone approach to the adaptive discovery of sensor-network topology

Hiroshi Tamaki, Ken Ichi Fukui, Masayuki Numao, Satoshi Kurihara

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

3 Citations (Scopus)

Abstract

Sensor-network technology is indispensable for constructing ubiquitous network infrastructures. Although information about adjacent relations between sensors is also very important for sensor networks, obtaining this information automatically without manual assistance is extremely difficult. Consequently, we propose a new methodology for constructing adjacent relations in sensor networks using an ant-colony optimization algorithm. This methodology can be used to automatically extract adjacent relations without using prepared sensor-location information or RFIDs to identify individual humans. We implemented a prototype system, and verified its basic effectiveness through simulations and an experiment using real data.

Original languageEnglish
Title of host publicationProceedings - 2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2008
Pages41-47
Number of pages7
DOIs
Publication statusPublished - 2008 Dec 1
Externally publishedYes
Event2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2008 - Sydney, NSW, Australia
Duration: 2008 Dec 92008 Dec 12

Publication series

NameProceedings - 2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2008

Other

Other2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2008
CountryAustralia
CitySydney, NSW
Period08/12/908/12/12

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

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  • Cite this

    Tamaki, H., Fukui, K. I., Numao, M., & Kurihara, S. (2008). Pheromone approach to the adaptive discovery of sensor-network topology. In Proceedings - 2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2008 (pp. 41-47). [4740594] (Proceedings - 2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2008). https://doi.org/10.1109/WIIAT.2008.143