Computer Science – Distributed – Parallel – and Cluster Computing
Scientific paper
2009-05-07
DAMAP 2009 (2009)
Computer Science
Distributed, Parallel, and Cluster Computing
Scientific paper
To accommodate the needs of large-scale distributed P2P systems, scalable data management strategies are required, allowing applications to efficiently cope with continuously growing, highly dis tributed data. This paper addresses the problem of efficiently stor ing and accessing very large binary data objects (blobs). It proposesan efficient versioning scheme allowing a large number of clients to concurrently read, write and append data to huge blobs that are fragmented and distributed at a very large scale. Scalability under heavy concurrency is achieved thanks to an original metadata scheme, based on a distributed segment tree built on top of a Distributed Hash Table (DHT). Our approach has been implemented and experimented within our BlobSeer prototype on the Grid'5000 testbed, using up to 175 nodes.
Antoniu Gabriel
Bougé Luc
Nicolae Bogdan
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