RDFS Rule based Parallel Reasoning Scheme for Large-Scale Streaming Sensor Data 


Vol. 41,  No. 9, pp. 686-698, Sep.  2014


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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.


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  Cite this article

[IEEE Style]

S. Kwon and Y. Park, "RDFS Rule based Parallel Reasoning Scheme for Large-Scale Streaming Sensor Data," Journal of KIISE, JOK, vol. 41, no. 9, pp. 686-698, 2014. DOI: .


[ACM Style]

SoonHyun Kwon and Youngtack Park. 2014. RDFS Rule based Parallel Reasoning Scheme for Large-Scale Streaming Sensor Data. Journal of KIISE, JOK, 41, 9, (2014), 686-698. DOI: .


[KCI Style]

권순현, 박영택, "대용량 스트리밍 센서데이터 환경에서 RDFS 규칙기반 병렬추론 기법," 한국정보과학회 논문지, 제41권, 제9호, 686~698쪽, 2014. DOI: .


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