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USENIX, The Advanced Computing Systems Association

NSDI '06 — Abstract

Pp. 45–58 of the Proceedings

Efficient Replica Maintenance for Distributed Storage Systems

Byung-Gon Chun, University of California, Berkeley; Frank Dabek, MIT Computer Science and Artificial Intelligence Laboratory; Andreas Haeberlen, Rice University/MPI-SWS; Emil Sit, MIT Computer Science and Artificial Intelligence Laboratory; Hakim Weatherspoon, University of California, Berkeley; M. Frans Kaashoek, MIT Computer Science and Artificial Intelligence Laboratory; John Kubiatowicz, University of California, Berkeley; Robert Morris, MIT Computer Science and Artificial Intelligence Laboratory


This paper considers replication strategies for storage systems that aggregate the disks of many nodes spread over the Internet. Maintaining replication in such systems can be prohibitively expensive, since every transient network or host failure could potentially lead to copying a server's worth of data over the Internet to maintain replication levels.

The following insights in designing an efficient replication algorithm emerge from the paper's analysis. First, durability can be provided separately from availability; the former is less expensive to ensure and a more useful goal for many wide-area applications. Second, the focus of a durability algorithm must be to create new copies of data objects faster than permanent disk failures destroy the objects; careful choice of policies for what nodes should hold what data can decrease repair time. Third, increasing the number of replicas of each data object does not help a system tolerate a higher disk failure probability, but does help tolerate bursts of failures. Finally, ensuring that the system makes use of replicas that recover after temporary failure is critical to efficiency.

Based on these insights, the paper proposes the Carbonite replication algorithm for keeping data durable at a low cost. A simulation of Carbonite storing 1 TB of data over a 365 day trace of PlanetLab activity shows that Carbonite is able to keep all data durable and uses 44% more network traffic than a hypothetical system that only responds to permanent failures. In comparison, Total Recall and DHash require almost a factor of two more network traffic than this hypothetical system.

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Last changed: 1 June 2006 ch