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Distributed data replication
and synchronization
Sponsor: NSF
Abstract
Many distributed applications in the current Internet are
massively replicated to ensure unsurpassed data robustness and scalability;
however, constant data churn (i.e., update of the source) and delayed
synchronization lead to staleness and thus lower performance in these systems.
The goal of this project is to pioneer a stochastic theory of data replication
that can tackle non-trivial dependency issues in synchronization of general
non-Poisson point processes, design more accurate sampling and prediction
algorithms for measuring data churn, solve novel multi-source and multi-replica
staleness-optimization problems, establish new fundamental understanding of
cooperative and multi-hop replication, and model non-stationary update processes
of real sources.
Journal
Papers
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X. Li, D.B.H. Cline, and D. Loguinov,
"Temporal Update Dynamics under Blind Sampling," IEEE/ACM Transactions on Networking,
vol. 25, no. 1, February 2017. |
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PDF |
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X. Li, D.B.H. Cline, and D. Loguinov,
"On Sample-Path Staleness in Lazy Data Replication," IEEE/ACM Transactions on Networking,
vol. 24, no. 5, October 2016. |
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PDF |
Conference
Papers
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D. Xiao, X. Li, D.B.H. Cline, and D. Loguinov, "Estimation
of DNS Source and Cache Dynamics under Interval-Censored Age Sampling," IEEE
INFOCOM, April 2018. |
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PDF,
PPT |
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X. Li, D.B.H. Cline, and D. Loguinov,
"Temporal Update Dynamics under Blind Sampling," IEEE INFOCOM, April
2015. |
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PDF,
PPT |
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X. Li, D.B.H. Cline, and D. Loguinov,
"On Sample-Path Staleness in Lazy Data Replication," IEEE INFOCOM, April
2015. |
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PDF,
PPT |
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X. Li and D. Loguinov, "Stochastic
Models of Pull-Based Data Replication in P2P Systems," IEEE P2P,
September 2014. |
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PDF,
PPT |
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