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Moving Object Tracking Scheme based on Polynomial Regression Prediction in Sparse Sensor Networks

저밀도 센서 네트워크 환경에서 다항 회귀 예측 기반 이동 객체 추적 기법

  • 황동교 (충북대학교 정보통신공학과) ;
  • 박혁 (충북대학교 정보통신공학과) ;
  • 박준호 (충북대학교 정보통신공학과) ;
  • 성동욱 (한국과학기술원) ;
  • 유재수 (충북대학교 정보통신공학과)
  • Received : 2011.12.20
  • Accepted : 2012.01.20
  • Published : 2012.03.28

Abstract

In wireless sensor networks, a moving object tracking scheme is one of core technologies for real applications such as environment monitering and enemy moving tracking in military areas. However, no works have been carried out on processing the failure of object tracking in sparse sensor networks with holes. Therefore, the energy consumption in the existing schemes significantly increases due to plenty of failures of moving object tracking. To overcome this problem, we propose a novel moving object tracking scheme based on polynomial regression prediction in sparse sensor networks. The proposed scheme activates the minimum sensor nodes by predicting the trajectory of an object based on polynomial regression analysis. Moreover, in the case of the failure of moving object tracking, it just activates only the boundary nodes of a hole for failure recovery. By doing so, the proposed scheme reduces the energy consumption and ensures the high accuracy for object tracking in the sensor network with holes. To show the superiority of our proposed scheme, we compare it with the existing scheme. Our experimental results show that our proposed scheme reduces about 47% energy consumption for object tracking over the existing scheme and achieves about 91% accuracy of object tracking even in sensor networks with holes.

무선 센서 네트워크 환경에서 이동 객체 추적 기법은 환경 모니터링이나 군사 지역에서 적의 이동을 추적하는 실제 응용을 위한 핵심적인 기반 기술이다. 기존 연구에서는 저밀도를 갖는 실제 센서 네트워크 환경에 의해 발생되는 감지 공백 영역을 고려하지 않았다. 따라서 많은 이동 객체 추적 실패가 발생하여 에너지 소모가 증가하였다. 이러한 문제를 해결하기 위해 본 논문에서는 저밀도 환경과 감지 공백 영역을 고려한 이동 객체 추적 기법을 제안한다. 제안하는 기법은 다항 회귀 분석을 이용해 객체의 경로를 예측하여 최소한의 센서 노드를 활성화시킨다. 또한 이동 객체 추적 실패가 발생할 경우 감지 공백 영역의 경계 노드만을 활성화 시키는 객체 추적 복구 기법을 수행한다. 이를 통해, 제안하는 기법은 에너지 소모량을 줄이고 감지 공백 영역 안에서도 높은 예측 정확도를 보장한다. 제안하는 기법이 기존 기법에 비해 이동 객체 추적에 소모되는 에너지를 평균 약 47% 감소시켰고, 센서 노드가 낮은 밀도로 배치된 상황에서 발생하는 감지 공백 영역에서도 평균 약 91%의 예측 정확도를 보였다.

Keywords

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