Online maintenance of very large random samples on flash storage

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Online maintenance of very large random samples on flash storage
Recent advances in flash media have made it an attractive alternative for data storage in a wide spectrum of computing devices, such as embedded sensors, mobile phones, PDA's, laptops, and even servers. However, flash media has many unique characteristics that make existing data management/analytics algorithms designed for magnetic disks perform poorly with flash storage. For example, while random (page) reads are as fast as sequential reads, random (page) writes and in-place data updates are orders of magnitude slower than sequential writes. In this paper, we consider an important fundamental problem that would seem to be particularly challenging for flash storage: efficiently maintaining a very large (100 MBs or more) random sample of a data stream (e.g., of sensor readings). First, we show that previous algorithms such as reservoir sampling and geometric file are not readily adapted to econd, we propose B-FILE, an energy-efficient abstraction for flash media to store self-expi...
Suman Nath, Phillip B. Gibbons
Added 28 Dec 2010
Updated 28 Dec 2010
Type Journal
Year 2008
Authors Suman Nath, Phillip B. Gibbons
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