PRUN : Eliminating Information Redundancy for Large Scale Data Backup System

Youjip Won, Rakie Kim, Jongmyeong Ban, Jungpil Hur, Sangkyu Oh, Jangsun Lee

2008 · 19 citations · 18 references

Concepts

TL;DR

File chunking for redundancy detection is the most time‑consuming task in backup. The study develops PRUN, a backup system that reduces latency and storage overhead by eliminating redundancy, and introduces an incremental modulo‑K algorithm to accelerate file chunking. PRUN is built with client and server modules that perform redundancy detection, fingerprint management, and chunk management, using an incremental modulo‑K algorithm to eliminate intra‑ and inter‑file redundancy and reduce chunking time. Experiments show that the incremental modulo‑K algorithm cuts file chunking latency by about 60 % and that PRUN’s redundancy elimination can cut backup storage by 80 % on successive Linux 2.6 kernel source versions.

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.

References

18