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Efficient Data Synchronization

This document outlines innovative approaches for efficient data synchronization, focusing on characteristic polynomial interpolation (CPI) techniques. It discusses full transfer methods, including Slow Sync and optimized algorithms for various scenarios. The implementation of GenSync software is highlighted, showcasing reconciliation experiments and performance analyses. Open problems and future directions are also presented, emphasizing the need for further research in interactive CPI and partitioning strategies. This work aims to contribute solutions to complex data synchronization challenges.

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Efficient Data Synchronization

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  1. Efficient Data Synchronization Jiaxi Jin

  2. OUTLINE Motivation Full Transfer 1 2 3 4 5 6 7 Characteristic Polynomial Interpolation(CPI) Generalized CPI Algorithm Software Implementation: GenSync Reconciliation Experiment Way to Go: Open Problems

  3. Motivation 1

  4. Full Transfer(Slow Sync) 2

  5. Characteristic Polynomial Interpolation(CPI) 3

  6. An Example of CPISync 3 send numerator

  7. Optimized CPI Algorithm with unknown m 4.1Probabilistic CPI : CPI with an unknown upper bound 4

  8. CPI(m=6) • failed: active partition Optimized CPI Algorithm with unknown m 4.2Partition CPI Recursively partitioning until succeed with a prescribed bound • CPI(m=6) • terminal 4 • CPI(m=6) • terminal

  9. Software Implementation: GenSync 5

  10. Reconciliation Experiment 6 6.1

  11. Reconciliation Experiment 6 6.2

  12. Reconciliation Experiment 6 6.3

  13. Reconciliation Experiment 6 6.4

  14. Reconciliation Experiment 6 6.5

  15. Reconciliation Experiment 6

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  20. Reconciliation Experiment 6 1

  21. Performance analysis and open problems will be added after extensive test 1

  22. Way to Go: Open Problems 7.1. Interactive CPI consumes extremely large CPUtime 7

  23. Way to Go: Open Problems 7

  24. Discussion Time THANKS

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