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ABSTRACT
Digital archives can best survive failures if they have made several c opies of their collections at remote sites. In this paper, we discuss how autonomous sites can cooperate to provide preservation by trading data. We examine the decisions that an archive must make when forming trading networks, such as the amount of storage space to provide and the best number of partner sites. We also deal with the fact that some sites may be more reliable than others. Experimental results from a data trading simulator illustrate which policies are most reliable. Our techniques focus on preserving the ``bits'' of digital collections; other services that focus on other archiving concerns (such as preserving meaningful metadata) can be built on top of the system we describe here.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 5
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Bruce R. Barkstrom , Melinda Finch , Michelle Ferebee , Calvin Mackey, Adapting digital libraries to continual evolution, Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries, July 14-18, 2002, Portland, Oregon, USA
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Mayank Bawa , Brian F. Cooper , Arturo Crespo , Neil Daswani , Prasanna Ganesan , Hector Garcia-Molina , Sepandar Kamvar , Sergio Marti , Mario Schlosser , Qi Sun , Patrick Vinograd , Beverly Yang, Peer-to-peer research at Stanford, ACM SIGMOD Record, v.32 n.3, September 2003
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INDEX TERMS
Primary Classification:
H.
Information Systems
H.3
INFORMATION STORAGE AND RETRIEVAL
General Terms:
Algorithms,
Design,
Documentation,
Human Factors,
Management,
Measurement,
Performance,
Reliability,
Theory
Keywords:
data trading,
digital archiving,
fault tolerance,
preservation,
replication
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