Journal of KIISE (정보과학회 논문지)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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RDFS Rule based Parallel Reasoning Scheme for Large-Scale Streaming Sensor Data

대용량 스트리밍 센서데이터 환경에서 RDFS 규칙기반 병렬추론 기법

  • Received : 2014.05.16
  • Accepted : 2014.07.03
  • Published : 2014.09.15
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Abstract

Recently, large-scale streaming sensor data have emerged due to explosive supply of smart phones, diffusion of IoT and Cloud computing technology, and generalization of IoT devices. Also, researches on combination of semantic web technology are being actively pushed forward by increasing of requirements for creating new value of data through data sharing and mash-up in large-scale environments. However, we are faced with big issues due to large-scale and streaming data in the inference field for creating a new knowledge. For this reason, we propose the RDFS rule based parallel reasoning scheme to service by processing large-scale streaming sensor data with the semantic web technology. In the proposed scheme, we run in parallel each job of Rete network algorithm, the existing rule inference algorithm and sharing data using the HBase, a hadoop database, as a public storage. To achieve this, we implement our system and evaluate performance through the AWS data of the weather center as large-scale streaming sensor data.

최근 스마트폰의 폭발적인 보급, IoT와 클라우드 컴퓨팅 기술의 고도화, 그리고 IoT 디바이스의 보편화로 대용량 스트리밍 센싱데이터가 출현하였다. 또한 이를 기반으로 데이터의 공유와 매쉬업 통해 새로운 데이터의 가치를 창출하기 위한 요구사항의 증대로 대용량 스트리밍 센싱데이터 환경에서 시맨틱웹 기술과의 접목에 관한 연구가 활발히 진행되고 있다. 하지만 데이터의 대용량성 스트리밍성으로 인해 새로운 지식을 도출하기 위한 지식 추론분야에서 많은 이슈들에 직면하고 있다. 이러한 배경하에, 본 논문에서는 IoT 환경에서 발생하는 대용량 스트리밍 센싱데이터를 시맨틱웹 기술로 처리하여 서비스하기 위해 RDFS 규칙기반 병렬추론 기법을 제시한다. 제안된 기법에서는 기존의 규칙추론 알고리즘인 Rete 알고리즘을 하둡프레임워크 맵리듀스를 통해 병렬로 수행하고, 공용 스토리지로서 하둡 데이터베이스인 HBase를 사용하여 데이터를 공유한다. 이를 위한 시스템을 구현하고, 대용량 스트리밍 센싱데이터인 기상청 AWS 관측데이터를 이용하여 제시된 기법에 대한 성능평가를 진행하고, 이를 입증한다.

Keywords

Acknowledgement

Grant : 개발형 시맨틱 USN서비스 플랫폼 기술개발

Supported by : 미래창조과학부

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