Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Localization Method in Wireless Sensor Networks using Fuzzy Modeling and Genetic Algorithm

퍼지 모델링과 유전자 알고리즘을 이용한 무선 센서 네트워크에서 위치추정

  • 윤숙현 (연세대학교 전기전자공학과) ;
  • 이제헌 (연세대학교 전기전자공학과) ;
  • 정우용 (연세대학교 전기전자공학과) ;
  • 김은태 (연세대학교 전기전자공학과)
  • Published : 2008.08.25
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Abstract

Localization is one of the fundamental problems in wireless sensor networks (WSNs) that forms the basis for many location-aware applications. Localization in WSNs is to determine the position of node based on the known positions of several nodes. Most of previous localization method use triangulation or multilateration based on the angle of arrival (AOA) or distance measurements. In this paper, we propose an enhanced centroid localization method based on edge weights of adjacent nodes using fuzzy modeling and genetic algorithm when node connectivities are known. The simulation results shows that our proposed centroid method is more accurate than the simple centroid method using connectivity only.

무선 센서 네트워크에서 노드들의 위치 측정 문제는 다양한 위치인식 기법을 적용하기 위해 기본적으로 해결해야 한다. 위치측정 문제는 위치가 알려진 일부 고정 노드들을 기준으로 나머지 노드들의 위치를 결정하는 문제이다. 기존의 대부분의 위치측정 기법은 고정 노드들로부터의 각도나 거리 측정값을 기반으로 삼각기법(triangulation) 이나 multilateration 방법을 사용한다. 본 논문에서는 노드들 간의 연결성이 알려져 있을 때 퍼지 모델링과 유전자 알고리즘을 사용하여 서로 전송범위 내에 있는 노드 쌍에 대해 가중치를 주어 미지 노드의 위치를 계산하는 향상된 중점 기법을 제안한다. 또한 시뮬레이션을 통해 제안된 중점 기법이 단순히 연결성만을 사용하는 중점 기법에 비해 정확한 위치측정이 가능함을 확인하였다.

Keywords

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