The Journal of Korea Institute of Information, Electronics, and Communication Technology (한국정보전자통신기술학회논문지)

Korea Information Electronic Communication Technology (한국정보전자통신기술학회)
권호 표지
DOI QR코드

DOI QR Code

Design of GlusterFS Based Big Data Distributed Processing System in Smart Factory

스마트 팩토리 환경에서의 GlusterFS 기반 빅데이터 분산 처리 시스템 설계

  • Received : 2018.01.29
  • Accepted : 2018.02.15
  • Published : 2018.02.28
Download PDF
⟨ Previous Next ⟩

Abstract

Smart Factory is an intelligent factory that can enhance productivity, quality, customer satisfaction, etc. by applying information and communications technology to the entire production process including design & development, manufacture, and distribution & logistics. The precise amount of data generated in a smart factory varies depending on the factory's size and state of facilities. Regardless, it would be difficult to apply traditional production management systems to a smart factory environment, as it generates vast amounts of data. For this reason, the need for a distributed big-data processing system has risen, which can process a large amount of data. Therefore, this article has designed a Gluster File System (GlusterFS)-based distributed big-data processing system that can be used in a smart factory environment. Compared to existing distributed processing systems, the proposed distributed big-data processing system reduces the system load and the risk of data loss through the distribution and management of network traffic.

스마트 팩토리는 설계 개발, 제조, 유통 물류 등 생산 전체 과정에 정보 통신 기술을 적용하여 생산성, 품질, 고객만족도 등을 향상시킬 수 있는 지능형 공장이다. 스마트 팩토리에서 발생되는 데이터의 양은 공장의 규모 및 시설 수준에 따라 많은 차이를 보이지만, 기존의 생산관리시스템을 활용하여 방대한 양의 데이터를 발생시키는 스마트 팩토리 환경에 적용하기에 어려움이 있다. 이로 인해 방대한 양의 빅데이터 처리할 수 있는 빅데이터 분산 처리 시스템의 필요성이 요구되고 있다. 따라서 본 논문에서는 스마트 팩토리 환경에서의 GlusterFS 기반 빅데이터 분산 처리 시스템 설계하였다. 제안하는 빅데이터 분산 처리 시스템은 기존 분산 처리 시스템에 비해 네트워크 트래픽 분산 및 관리를 통해 부하와 데이터 소실 위험도를 감소시켰다.

Keywords

References

  1. Hye-Jung Chang and Do-Nyun Kim, "A Study on big data utilization for implementation of the resident participation type safe community planning of the smart city," Journal of Korea Institute of Information, Electronics, and Communication Technology, Vol. 9, No. 5, pp. 478-495, Oct, 2016. https://doi.org/10.17661/jkiiect.2016.9.5.478
  2. In-Hak Joo, "Spatial Big Data Query Processing System Supporting SQL-based Query Language in Hadoop," Journal of Korea Institute of Information, Electronics, and Communication Technology, Vol. 10, No. 1, pp. 1-8, Feb, 2017. https://doi.org/10.17661/jkiiect.2017.10.1.1
  3. Eun-Hee Jeong and Byung-Kwan Lee, "A Design of Hadoop Security Protocol using One Time Key based on Hash-chain," Journal of Korea Institute of Information, Electronics, and Communication Technology, Vol. 10, No. 4, pp. 340-349, Aug, 2017. https://doi.org/10.17661/jkiiect.2017.10.4.340
  4. Jae-Hyuck Kwak, Sangwan Kim, Taesang Huh and Soonwook Hwang, "Implementation and Performance Analysis of Hadoop MapReduce over Lustre Filesystem," KIISE Transactions on Computing Practices, Vol. 21, No. 8, pp. 561-566, Aug, 2015. https://doi.org/10.5626/KTCP.2015.21.8.561
  5. Deoksang Kim, Hyeonsang Eom and Heonyoung Yeom, "Performance Optimization in GlusterFS on SSDs," KIISE Transactions on Computing Practices, Vol. 22, No. 2, pp. 95-100, Feb, 2016. https://doi.org/10.5626/KTCP.2016.22.2.95