최근의 빅데이터, 머신러닝, 클라우드 컴퓨팅 분야의 성장에 따라 대용량의 비정형 데이터를 저장할 수 있는 스토리지의 중요성은 날로 커지고 있다. 이에 따라 MAHA-FS, GlusterFS, Ceph 등의 개방형 하드웨어 기반의 분산파일시스템 기술이 많은 주목을 받고 있다. 이러한 저비용 분산 파일시스템들은 데이터의 내결함성을 보장하기 위하여 초기에 복제 방식을 사용하였으나, 스토리지의 용량이 커질수록 복제 방식이 가지는 스토리지 공간의 저효율성이 점차 부각되면서 이를 보완하려는 방향으로 연구가 진행되고 있다. 본 논문은 복제방식을 대체하여 스토리지공간 효율성을 향상시킬 수 있는 소거코딩 기법을 MAHA-FS 분산 파일시스템에 적용하여 스토리지의 효율성을높이고, 소거코딩 지원에 따라 발생하는 데이터 일관성 문제를 해결하는 효율적인 방식으로 VDelta 기법을 제안하고 적용하였다. 본 논문은 MAHA-FS와 GlusterFS의 소거코딩의 구조적 차이점을 기술하고 두 파일시스템의 성능을 비교하여 MAHA-FS의 소거코딩 성능이 GlusterFS에 비해 우수함을 확인하였다.
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