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세부 동작 기반 사물인터넷 서비스 분류 기법 개발

Development of IoT Service Classification Method based on Service Operation Characteristic

  • Jo, Jeong hoon (Dept. of Computer Engineering, Seokyeong Univ.) ;
  • Lee, HwaMin (Dept. of Computer Software Engineering, Soonchunhyang Univ.) ;
  • Lee, Dae won (Dept. of Computer Engineering, Seokyeong Univ.)
  • 투고 : 2018.01.05
  • 심사 : 2018.01.17
  • 발행 : 2018.04.30

초록

최근 사물인터넷 서비스의 등장 및 융합으로 통합 사물인터넷 서비스 플랫폼에 관한 다양한 연구가 진행되었다. 현재 사물인터넷 서비스는 서비스 제공자의 목적에 따라 독립적인 시스템으로 구축되어 유사한 서비스를 제공하는 서비스 간의 정보 교환 및 모듈 재사용이 불가능 하였다. 이에 본 연구에서는 통합 사물인터넷 플랫폼 환경을 제공하기 위하여 다양한 서비스들의 세부 동작 기반 서비스 분류 알고리즘을 제안한다. 구현을 통하여 상용화된 100여개의 사물인터넷 서비스를 분류 및 군집화를 진행하였으며 이를 기반으로 K-means알고리즘과 비교하여 제안하는 알고리즘의 성능을 평가하였다. 또한 표본 집단의 부족으로 발생하는 단일 클러스터를 방지하기 위하여 K-means 알고리즘을 활용하여 재 군집화를 진행하였다. 향후 연구로 기존의 서비스 표본 집단을 확대하고 현재 구현한 분류 시스템을 보다 빠르고 대량의 데이터 처리를 위하여 스파크를 활용할 예정이다.

Recently, through the emergence and convergence of Internet services, the unified Internet of thing(IoT) service platform have been researched. Currently, the IoT service is constructed as an independent system according to the purpose of the service provider, so information exchange and module reuse are impossible among similar services. In this paper, we propose a operation based service classification algorithm for various services in order to provide an environment of unfied Internet platform. In implementation, we classify and cluster more than 100 commercial IoT services. Based on this, we evaluated the performance of the proposed algorithm compared with the K-means algorithm. In order to prevent a single clustering due to the lack of sample groups, we re-cluster them using K-means algorithm. In future study, we will expand existing service sample groups and use the currently implemented classification system on Apache Spark for faster and more massive data processing.

키워드

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