As a space-efficient approach to data archive and backup, data deduplication is becoming increasingly popular in storage systems. However, as the data growing rapidly in data centers, single-node storage node is no longer be able to provide the corresponding throughput and capacities as expected. Building deduplication clusters is considered as a promising strategy to leverage such bottle-neck on single-node system. However, deduplication relies on how much the system knows about information of previous stored data. The single-node system obviously obtains all such information and is able to detect duplicate data there; however storage nodes in cluster-based system cannot know information on other nodes. It is nontrivial to route data intelligently enough so that the system could support deduplication performance comparable to that of a single-node system, while also at a trivial cost. In this paper, we propose an elastic data routing strategy, aiming to achieve deduplication performance comparable to state-of-the-art, while require much less computation resources.
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