%0 Conference Proceedings
%T DASM: A Dynamic Adaptive Forward Assembly Area Method to Accelerate Restore Speed for Deduplication-Based Backup Systems
%+ Shanghai Jiao Tong University [Shanghai]
%+ Université de Tsukuba = University of Tsukuba
%A Tan, Chao
%A Li, Luyu
%A Wu, Chentao
%A Li, Jie
%Z Part 2: Resilience and Reliability
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 13th IFIP International Conference on Network and Parallel Computing (NPC)
%C Xi'an, China
%Y Guang R. Gao
%Y Depei Qian
%Y Xinbo Gao
%Y Barbara Chapman
%Y Wenguang Chen
%I Springer International Publishing
%3 Network and Parallel Computing
%V LNCS-9966
%P 58-70
%8 2016-10-28
%D 2016
%R 10.1007/978-3-319-47099-3_5
%K Data deduplication
%K Restore speed
%K Reliability
%K Cache policy
%K Performance evaluation
%Z Computer Science [cs]Conference papers
%X Data deduplication yields an important role in modern backup systems for its demonstrated ability to improve storage efficiency. However, in deduplication-based backup systems, the consequent exhausting fragmentation problem has drawn ever-increasing attention over in terms of backup frequencies, which leads to the degradation of restoration speed. Various Methods are proposed to address this problem. However, most of them purchase restore speed at the expense of deduplication ratio reduction, which is not efficient.In this paper, we present a Dynamic Adaptive Forward Assembly Area Method, called DASM, to accelerate restore speed for deduplication-based backup systems. DASM exploits the fragmentation information within the restored backup streams and dynamically trades off between chunk-level cache and container-level cache. DASM is a pure data restoration module which pursues optimal read performance without sacrificing deduplication ratio. Meanwhile, DASM is a resource independent and cache efficient scheme, which works well under different memory footprint restrictions. To demonstrate the effectiveness of DASM, we conduct several experiments under various backup workloads. The results show that, DASM is sensitive to fragmentation granularity and can accurately adapt to the changes of fragmentation size. Besides, experiments also show that DASM improves the restore speed of traditional LRU and ASM methods by up to 58.9 % and 57.1 %, respectively.
%G English
%Z TC 10
%Z WG 10.3
%2 https://inria.hal.science/hal-01647993/document
%2 https://inria.hal.science/hal-01647993/file/432484_1_En_5_Chapter.pdf
%L hal-01647993
%U https://inria.hal.science/hal-01647993
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC10
%~ IFIP-NPC
%~ IFIP-WG10-3
%~ IFIP-LNCS-9966