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Efficient Metadata Management in Large Distributed Storage Systems††This research is supported by Lawrence Livermore National Laboratory, Los Alamos National Laboratory, and Sandia National Laboratory under contract 520714.

Abstract

Efficient metadata management is a critical aspect of overall system performance in large distributed storage systems. Directory subtree partitioning and pure hashing are two common techniques used for managing metadata in such systems, but both suffer from bottlenecks at very high concurrent access rates. We present a new approach called Lazy Hybrid (LH) metadata management that combines the best aspects of these two approaches while avoiding their shortcomings.

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