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Most Influential SIGCOMM 2019 Paper · 2026-03 edition

Graphene: Efficient Interactive Set Reconciliation Applied To Blockchain Propagation

A. Pinar Ozisik, Gavin Andresen, Brian N. Levine, Darren Tapp, George Bissias, Sunny Katkuri

Venue
ACM SIGCOMM Conference (SIGCOMM) 2019
Recognition
Most Influential SIGCOMM 2019 Paper (Rank No. 12)
Edition
2026-03
Impact factor
4
Certificate ID
f73dc8c55f59aba5

Abstract

We introduce Graphene, a method and protocol for interactive set reconciliation among peers in blockchains and related distributed systems. Through the novel combination of a Bloom filter and an Invertible Bloom Lookup Table (IBLT), Graphene uses a fraction of the network bandwidth used by deployed work for one- and two-way synchronization. We show that, for this specific problem, Graphene is more efficient at reconciling n items than using a Bloom filter at the information theoretic bound. We contribute a fast and implementation-independent algorithm for parameterizing an IBLT so that it is optimally small in size and meets a desired decode rate with arbitrarily high probability. We characterize our performance improvements through analysis, detailed simulation, and deployment results for Bitcoin Cash, a prominent cryptocurrency. Our implementations of Graphene, IBLTs, and our IBLT optimization algorithm are all open-source code.

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