KIPS Transactions on Software and Data Engineering (정보처리학회논문지:소프트웨어 및 데이터공학)

Korea Information Processing Society (한국정보처리학회)
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A Method to Provide Context from Massive Data Processing in Context-Aware System

상황인지 시스템에서 대용량의 데이터 처리결과를 컨텍스트 정보로 제공하기 위한 방법

  • Received : 2018.11.29
  • Accepted : 2019.02.20
  • Published : 2019.04.30
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Abstract

Unlike a single value from a sensor device, a massive data set has characteristics for various processing aspects; input data may be formed in a different format, the size of input data varies, and the processing time of analyzing input data is not predictable. Therefore, context aware systems may contain complex modules, and these modules can be implemented and used in different ways. In order to solve these problems, we propose a method to handle context information from the result of analyzing massive data. The proposed method considers analysis work as a different type of abstracting context and suggests the way of representing context information. In experiment, we demonstrate how the context processing engine works properly in a couple of steps with healthcare services.

단일 센서기기로부터 수집된 데이터와는 다르게 대용량의 데이터는 입력데이터의 구성 및 크기가 가변적이고, 처리 완료시점을 예측할 수 없는 특징을 갖고 있다. 상황인지 시스템이 이러한 환경의 요구사항을 적용하게 되면 컨텍스트 표현방법과 처리모듈들이 개별로 구성되어 해당 입력자료에 대한 호출 및 처리루틴이 복잡하게 구현될 수 있는 문제점이 있다. 이러한 문제점을 해결하기 위해서 본 논문에서 제안하는 처리방법은 온톨로지 기반의 지식표현을 통해 컨텍스트를 표현하고, 대용량의 데이터 처리결과를 반환하는 모듈의 중복 실행을 방지하여 컨텍스트 정보를 제공하기 위한 동작순서를 함께 기술한다. 실험에서는 헬스케어 환경에서 발생하는 센싱데이터 중 대용량의 데이터 처리결과를 필요로 하는 서비스에 대해 기술하고, 기존의 센싱데이터를 바탕으로 서비스를 제공하는 처리과정과 함께 대용량의 데이터 처리결과를 컨텍스트 정보로 제공하는 과정을 보인다.

Keywords

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Fig. 1. Layered Architecture of Context-aware System for Healthcare Services

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Fig. 2. Conceptual Procedure for Context Abstraction from Sensor Devices

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Fig. 3. Sequence Diagram for Processing Responsive Collected Data

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Fig. 4. Sequence Diagram for Processing Unresponsive Collected Data

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Fig. 5. Webpage for Users to Explore the List and Histories of Context Information

Table 1. Summary for healthcare service scenario examples

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Table 2. Service Summary with Context Representation for the Experiments

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Table 3. Summary of Input Devices for Experiments

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Table 4. Features and Input and Output Data for Context Processing Engine

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