DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING | DWIGHT LOOK COLLEGE OF ENGINEERING | TEXAS A&M UNIVERSITY

 

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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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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.

PDF

Conference Papers

 
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X. Li, D.B.H. Cline, and D. Loguinov, "Temporal Update Dynamics under Blind Sampling," IEEE INFOCOM, April 2015.

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.

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.

PDF, PPT
 


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