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A Clustering Scheme Considering the Structural Similarity of Metadata in Smartphone Sensing System

스마트폰 센싱에서 메타데이터의 구조적 유사도를 고려한 클러스터링 기법

  • 민홍 (호서대학교, 컴퓨터정보공학부) ;
  • 허준영 (한성대학교, 컴퓨터공학과)
  • Received : 2014.09.29
  • Accepted : 2014.12.12
  • Published : 2014.12.31

Abstract

As association between sensor networks that collect environmental information by using numberous sensor nodes and smartphones that are equipped with various sensors, many applications understanding users' context have been developed to interact users and their environments. Collected data should be stored with XML formatted metadata containing semantic information to share the collected data. In case of distance based clustering schemes, the efficiency of data collection decreases because metadata files are extended and changed as the purpose of each system developer. In this paper, we proposed a clustering scheme considering the structural similarity of metadata to reduce clustering construction time and improve the similarity of metadata among member nodes in a cluster.

다수의 저가 센서 노드를 통해 주변의 환경 정보를 수집하는 센서 네트워크와 스마트폰에 탑재되어 있는 다양한 종료의 센서들을 연동함으로써 사용자의 상태에 따라 주위 환경과 반응하는 응용들이 개발되고 있다. 이런 응용에서 수집된 데이터의 공유를 위해 센싱 데이터와 의미정보를 저장하는 XML 형태의 메타데이터를 함께 저장할 필요가 있다. 메타데이터는 시스템 설계자의 필요에 따라 확장되고 변형되는데 거리 기반의 클러스터링 기법을 사용할 경우 서로 다른 형태의 메타데이터가 혼재하게 되어 데이터 수집의 효율성이 떨어지는 문제가 발생한다. 본 논문에서는 효율적인 데이터 수집을 위해 클러스터를 구성할 때 각 노드의 메타데이터의 구조적 유사도를 반영함으로써 클러스터 구성에 필요한 시간을 줄이고, 구성원 간 메타데이터 유사도를 향상시키는 기법을 제안한다.

Keywords

References

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