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- W2277173623 abstract "최근 빅데이터 분야에서 데이터를 메모리에 적재 후 빠르게 처리하는 인메모리 컴퓨팅 기술이 새롭게 부각되고 있다. 인메모리 컴퓨팅 기술은 과거 대용량 메모리와 다중 프로세서를 탑재한 고성능서버에 적용 가능하였지만, 점차 일반 컴퓨터를 초고속 네트워크로 연결하여 분산 병렬처리가 가능한 구조로 변화하고 있다. 본 논문은 In-memory data grid (IMDG) 기술을 택시 애플리케이션에 접목하여 기존의 데이터베이스의 변경 없이 성능을 향상시키는 기법을 제안한다. IMDG 기술을 적용한 경우 기존의 데이터베이스 기반의 웹서비스에 비해 처리속도와 처리량이 평균 6~9배정도 증가하며, 또한 부하량에 따른 처리량 변화의 폭이 매우 작음을 확인 하였다. Recent studies in Big Data Analysis are showing promising results, utilizing the main memory for rapid data processing. In-memory computing technology can be highly advantageous when used with high-performing servers having tens of gigabytes of RAM with multi-core processors. The constraint in network in these infrastructure can be lessen by combining in-memory technology with distributed parallel processing. This paper discusses the research in the aforementioned concept applying to a test taxi hailing application without disregard to its underlying RDBMS structure. The application of IMDG technology in the application's backend API without restructuring the database schema yields 6 to 9 times increase in performance in data processing and throughput. Specifically, the change in throughput is very small even with increase in data load processing." @default.
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- W2277173623 date "2015-09-30" @default.
- W2277173623 modified "2023-09-24" @default.
- W2277173623 title "Enhancing the performance of taxi application based on in-memory data grid technology" @default.
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- W2277173623 doi "https://doi.org/10.7465/jkdi.2015.26.5.1035" @default.
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