DocumentCode
2076558
Title
PRUN : Eliminating Information Redundancy for Large Scale Data Backup System
Author
Won, Youjip ; Kim, Rakie ; Ban, Jongmyeong ; Hur, Jungpil ; Oh, Sangkyu ; Lee, Jangsun
Author_Institution
Dept. of Electron. & Comput. Eng., Hanyang Univ., Seoul
fYear
2008
fDate
June 30 2008-July 3 2008
Firstpage
139
Lastpage
144
Abstract
In this work, we develop novel backup system, PRUN, for massive scale data storage. PRUN aims at improving the backup latency and storage overhead of backup via effectively eliminating information redundancy in the files. PRUN eliminates intra-file and inter-file information redundancy. PRUN consists of client module and server module. PRUN consists of three key technical ingredients: redundancy detection, fingerprint manager, and chunk manager. File chunking for redundancy detection is the most time consuming task in backup. For efficient file chunking, we develop incremental modulo-K algorithm which enables us to improve the file chunking time significantly. We perform various experiment to measure the overhead of each tasks in backup operation and to examine the efficiency of redundancy elimination. Incremental modulo-K reduces the file chunking latency by approximately 60%. Redundancy elimination scheme can reduce the storage requirement of backup by 80% when we backup different minor versions of Linux 2.6 kernel source.
Keywords
data handling; Linux 2.6 kernel source; backup latency; chunk manager; file chunking latency; fingerprint manager; incremental modulo-K algorithm; information redundancy; interfile information redundancy; large scale data backup system; massive scale data storage; redundancy detection; Application software; Bandwidth; Delay; File systems; Fingerprint recognition; Large-scale systems; Law; Legal factors; Partitioning algorithms; Video compression; backup; de-duplication;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Sciences and Its Applications, 2008. ICCSA '08. International Conference on
Conference_Location
Perugia
Print_ISBN
978-0-7695-3243-1
Type
conf
DOI
10.1109/ICCSA.2008.46
Filename
4561214
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