Journal of Internet of Things and Convergence (사물인터넷융복합논문지)

The Korea Internet of Things Society (한국사물인터넷학회)
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A Design of Hot Data Classifier and Management Scheme for An Efficient Resource Management

효율적인 자원 관리를 위한 핫데이터 분류기 및 관리 정책 설계

  • Hyun-Seob Lee (Division of Computer Engineering, Baekseok University)
  • 이현섭 (백석대학교 컴퓨터공학부)
  • Received : 2023.08.08
  • Accepted : 2023.10.09
  • Published : 2023.10.31
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Abstract

Hot data is frequently used data that affects the performance and lifespan of a storage system. Therefore, classifying and managing the identified hot data is important for the performance and lifetime of storage devices, especially for NAND flash memory, which is characterized by rapid degradation after repeated intensive write operations to specific blocks. In this paper, we design a hot data classifier and management scheme for an efficient resource management in flash memory-based storage devices by benchmarking traces extracted from enterprise servers. Also, we propose a method to measure the frequency of hot data using multiple hashes, and to improve the performance and lifetime of the storage system by classifying the identified hot data and managing it on degradation-resistant media. Finally, we demonstrate the effectiveness of the proposed method by measuring the increased performance and lifetime through experiments.

핫데이터는 저장시스템의 성능과 수명에 영향을 주는 사용 빈도가 높은 데이터이다. 따라서 식별된 핫데이터를 분류하여 관리하는 것은 저장장치의 성능과 수명을 위해 중요한 일이다. 특히 특정 블록에 집중적인 쓰기 동작을 반복하면 열화 현상이 급격하게 진행되는 특징을 가지고 있는 낸드 플래시 메모리는 이러한 핫데이터를 구분하여 관리하는 것이 성능과 수명을 향상하기 위해 필요하다. 본 논문에서는 엔터프라이즈 서버에서 추출한 트레이스를 벤치마킹하여 플래시 메모리 기반 저장장치에서 자원을 효율적으로 관리하는데 필요한 핫데이터 분류기 및 관리 정책을 설계한다. 또한. 멀티 해시를 이용하여 핫데이터의 빈도를 측정하고, 식별된 핫데이터를 구분하여 열화에 강한 미디어에 관리하는 기법을 통해 저장시스템의 성능과 수명을 향상시키는 방법을 제안한다. 마지막으로 실험을 통해 증가한 성능과 수명을 측정하여 제안하는 방법의 효과를 증명한다.

Keywords

Acknowledgement

This paper was supported by 2023 Baekseok University Research Fund

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