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ABSTRACT
 Proceedings of the 4th USENIX Conference on File and Storage Technology (FAST '05). San Francisco, CA.
December 13-16, 2005.
Supercedes Carnegie Mellon University Parallel Data Lab Technical Report CMU-PDL-05-104, April, 2005. Ursa Minor: Versatile Cluster-based Storage
Michael Abd-El-Malek, William V. Courtright II, Chuck Cranor, Gregory R. Ganger,
James Hendricks, Andrew J. Klosterman, Michael Mesnier, Manish Prasad,
Brandon Salmon, Raja R. Sambasivan, Shafeeq Sinnamohideen, John D. Strunk, Eno Thereska, Matthew Wachs, Jay J. Wylie
Carnegie Mellon University
Pittsburgh, PA 15213
chensm@cs.cmu.edu
http://www.pdl.cmu.edu/
No single encoding scheme or fault model is optimal
for all data. A versatile storage system allows them to
be matched to access patterns, reliability requirements,
and cost goals on a per-data item basis. Ursa Minor is
a cluster-based storage system that allows data-specific
selection of, and on-line changes to, encoding schemes
and fault models. Thus, different data types can share a
scalable storage infrastructure and still enjoy specialized
choices, rather than suffering from “one size fits all.” Experiments
with Ursa Minor show performance benefits
of 2–3× when using specialized choices as opposed to
a single, more general, configuration. Experiments also
show that a single cluster supporting multiple workloads
simultaneously is much more efficient when the choices
are specialized for each distribution rather than forced
to use a “one size fits all” configuration. When using
the specialized distributions, aggregate cluster throughput
nearly doubled.
FULL PAPER (conference version): pdf
FULL PAPER (technical report version): pdf
 
pdl-webmaster@ece.cmu.edu
Last updated
11 October, 2005
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