論文

査読有り
2009年2月

Data Gathering Scheme Using Chaotic Pulse-Coupled Neural Networks for Wireless Sensor Networks

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES
  • Hidehiro Nakano
  • ,
  • Akihide Utani
  • ,
  • Arata Miyauchi
  • ,
  • Hisao Yamamoto

E92A
2
開始ページ
459
終了ページ
466
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1587/transfun.E92.A.459
出版者・発行元
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG

Wireless sensor networks (WSNs) have attracted a significant amount of interest from many researchers because they have great potential as a means of obtaining information of various environments remotely. WSNs have a wide range of applications, such as natural environmental monitoring in forest regions and environmental control in office buildings. In WSNs, hundreds or thousands of micro-sensor nodes with such resource limitations as battery capacity, memory, CPU, and communication capacity are deployed without control in a region and used to monitor and gather sensor information of environments. Therefore, a scalable and efficient network control and/or data gathering scheme for saving energy consumption of each sensor node is needed to prolong WSN lifetime. In this paper, assuming that sensor nodes synchronize to intermittently communicate with each other only when they are active for realizing the long-term employment of WSNs, we propose a new synchronization scheme for gathering sensor information using chaotic pulse-coupled neural networks (CPCNN). We evaluate the proposed scheme using computer simulations and discuss its development potential. In simulation experiments, the proposed scheme is compared with a previous synchronization scheme based on a pulse-coupled oscillator model to verify its effectiveness.

リンク情報
DOI
https://doi.org/10.1587/transfun.E92.A.459
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000265701000016&DestApp=WOS_CPL
ID情報
  • DOI : 10.1587/transfun.E92.A.459
  • ISSN : 1745-1337
  • Web of Science ID : WOS:000265701000016

エクスポート
BibTeX RIS