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Data deduplication has gained increasing attention and popularity as a space-efficient approach in backup storage systems. One of the main challenges for centralized data deduplication is the scalability of fingerprint-index search. In this paper, we propose SiLo, a near-exact and scalable deduplication system that effectively and complementarily exploits similarity and locality of data streams to achieve high duplicate elimination, throughput, and well balanced load at extremely low RAMdoi:10.1109/tc.2014.2308181 fatcat:szqge3jt5zhsnnnn7yhntj64j4