서지주요정보
SDIO에서 RAID 레벨 5의 효율적인 구현 = Efficient implementation of RAID level 5 on single disk I/O
서명 / 저자 SDIO에서 RAID 레벨 5의 효율적인 구현 = Efficient implementation of RAID level 5 on single disk I/O / 김호진.
저자명 김호진 ; Ghim, Ho-Jin
발행사항 [대전 : 한국과학기술원, 2004].
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소장정보

등록번호

8015263

소장위치/청구기호

학술문화관(문화관) 보존서고

MCS 04017

SMS전송

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초록정보

Single Disk I/O(SDIO) can bring into cluster computing environment fast and reliable distributed storage. The data distribution scheme used for SDIO was mainly RAID level 0 or RAID level 1 for now. By using RAID level 5 scheme for SDIO instead of RAID level 0 or 1, one can achieve good performance, good reliability and high disk space utilization simultaneously. But RAID level 5 also has some weak points. Those are network overhead problem, small write problem, and write sharing problem. We suggest four approaches to solve those problems, or at least alleviate them. The names of the approaches are Datanode-based Parity Computation, Distributed Parity Computation, Parity Queuing, Parity Cumulating. The first two of them manage network overhead problem. Eventually Distributed Parity Computation minimizes the number of network messages to two messages by dividing parity computation into two computation, one for data node and the other for parity node. Parity Queuing attacks small write problem by delaying two of four disk access operations until disk idle time. Parity Cumulating improves buffer requirement of Parity Queuing and reduces operations for idle time. We experimented each approaches for sequential data and for random data. The approaches are compared to Naive Method. Naive Method is the simplest method designed without any optimization techniques. As a result, Distributed Parity Computation reduced disk I/O operation time by 12% in respect to Naive Method. Also, Parity Queuing adds more reduction of disk I/O operation time by 11% in respect to Distributed Parity Computation. Parity Cumulating reduces parity buffer size of Parity Queuing. With sequential data, the parity buffer size is reduced by 33% in respect to Parity Queuing. With random data, the parity buffer size is reduced by 3%.

서지기타정보

서지기타정보
청구기호 {MCS 04017
형태사항 vi, 34 p. : 삽도 ; 26 cm
언어 한국어
일반주기 저자명의 영문표기 : Ho-Jin Ghim
지도교수의 한글표기 : 윤현수
지도교수의 영문표기 : Hyun-Soo Yoon
학위논문 학위논문(석사) - 한국과학기술원 : 전산학전공,
서지주기 참고문헌 수록
주제 단일 디스크 입출력
레이드
클러스터
SINGLE DISK I/O
RAID
CLUSTER
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