Authors: Lei Yang, Yossi Gilad, Mohammad Alizadeh
Published on: February 05, 2024
Impact Score: 8.3
Arxiv code: Arxiv:2402.02668
Summary
- What is new: Introduction of Rateless Invertible Bloom Lookup Tables (Rateless IBLT) for set reconciliation, achieving low computation and near-optimal communication costs.
- Why this is important: The existing set reconciliation processes are inefficient in terms of computation and communication costs.
- What the research proposes: Rateless IBLT uses an encoder for incrementally encoding set differences into an infinite stream, optimizing both computation and communication costs.
- Results: Rateless IBLT demonstrated 3–4x lower communication and 2–2000x lower computation costs than existing schemes, with a real-world application to Ethereum showing 5.6x faster completion and 4.4x less communication cost.
Technical Details
Technological frameworks used: Rateless error-correcting codes
Models used: Invertible Bloom Lookup Tables (IBLT)
Data used: Ethereum blockchain state data
Potential Impact
Blockchain systems, distributed computing platforms, data synchronization services
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