The Journal of The Korea Institute of Intelligent Transport Systems (한국ITS학회 논문지)

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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Implementation of High Speed Big Data Processing System using In Memory Data Grid in Semiconductor Process

반도체 공정에서 인 메모리 데이터 그리드를 이용한 고속의 빅데이터 처리 시스템 구현

  • Received : 2016.05.31
  • Accepted : 2016.07.22
  • Published : 2016.10.31
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Abstract

Data processing capacity and speed are rapidly increasing due to the development of hardware and software in recent time. As a result, data usage is geometrically increasing and the amount of data which computers have to process has already exceeded five-thousand transaction per second. That is, the importance of Big Data is due to its 'real-time' and this makes it possible to analyze all the data in order to obtain accurate data at right time under any circumstances. Moreover, there are many researches about this as construction of smart factory with the application of Big Data is expected to have reduction in development, production, and quality management cost. In this paper, system using In-Memory Data Grid for high speed processing is implemented in semiconductor process which numerous data occur and improved performance is proven with experiments. Implemented system is expected to be possible to apply on not only the semiconductor but also any fields using Big Data and further researches will be made for possible application on other fields.

최근 하드웨어와 소프웨어의 발전으로 데이터의 처리 용량과 처리 속도도 급속하게 증가하고 있다. 이로 인한 데이터 사용량은 기하급수적으로 증가하고 있으며, 이미 컴퓨터가 처리해야하는 자료는 초당 5천 트랜잭션을 넘었다. 이처럼 빅데이터가 중요한 이유는 실시간 때문이며, 이는 어떠한 상황에서도 모든 데이터를 분석하여 정확한 데이터를 적시에 얻을 수 있기 때문이다. 또한, 빅데이터를 활용한 스마트 공장을 만들면 개발 및 생산비용, 품질관리 비용 감소효과가 있을 것으로 예상하고 많은 연구가 수행되고 있다. 본 논문에서는 많은 데이터들이 발생하는 반도체 공정에서 고속의 빅데이터 처리를 위한 인-메모리 데이터 그리드를 이용한 시스템을 구현하였으며, 실험을 통해 향상된 성능을 입증하였다. 구현한 시스템은 반도체 뿐 만 아니라 빅데이터를 사용하는 모든 부분에서 응용 가능 할 것으로 판단된다.

Keywords

References

  1. Lee S. H.(2012), "Utilization of big data," Journal of Advanced Information Technology and Convergence, vol. 10, no. 3, pp.51-54.
  2. Lee H. S., Lee M. Y., Kim C. S. and Heo S. J.(2013), "Trends of In-Memory Database Management System Technology," 2013 Electronics and Telecommunications Trends, pp.33-41.
  3. Pezzini M., Claunch C and Unsworth J.(2012), "Top 10 Strategic Technology Trends : In Memory Computing," Gartner.
  4. Ahn C. W. and Hwang S. K.(2012), "Big Data Technology and Main Issue," Journal of Communications of KIISE, vol. 30, no. 6, pp.10-17.
  5. IDC.(2012), "Worldwide Big Data Technology and Service 2012-2015 Forecast," IDC2012.
  6. Park J. B., Lee A. and Kim T.(2016), " Proposal for High Speed Big Data Processing System Structure using In Memory Data Grid in Semiconductor Process," Journal of The 2016 Korea Institute of Intelligent Transport Systems Conference, pp.335-337.
  7. Park J. B., Lee A. and Kim T.(2016), "A Study on High Speed Big Data Loseless Scheme of Semiconductor Process using In Memory Data Grid," Journal of The 2016 Korea Institute of Intelligent Transport Systems Conference, pp.338-340.
  8. Pezzini M.(2011), "Net IT Out : In-Memory Computing - Thinking the Unthinkable Applications," Gartner Symposium 2011.
  9. Mckinsey Global Institute.(2011), "Big Data : The next frontier for innovation, competition and productivity," Mckinsey&Company Report.

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