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In Big Data era, the gap between the storage performance and application's I/O requirement is increasingly enlarged. I/O congestion caused by concurrent storage accesses from multiple applications is inevitable, and therefore severely harms the performance. Conventional approaches either focus on optimizing an application's access pattern individually or handle I/O requests on low-level storage layer without any knowledge from the upper-level applications. In this paper, we present a noveldoi:10.1109/cluster.2015.45 dblp:conf/cluster/ZhouYZRTWL15 fatcat:p7orvdwhlvc4ti4grlizgalg6m