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Dynamic Probabilistic Reliable Broadcast

Authors João Paulo Bezerra , Veronika Anikina, Petr Kuznetsov , Liron Schiff, Stefan Schmid

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Author Details

João Paulo Bezerra
  • LTCI, Télécom Paris, Institut Polytechnique de Paris, France
Veronika Anikina
  • ITMO University, St. Petersburg, Russia
Petr Kuznetsov
  • LTCI, Télécom Paris, Institut Polytechnique de Paris, France
Liron Schiff
  • Akamai Technologies, Cambridge, MA, USA
Stefan Schmid
  • Technische Universität Berlin, Germany

Acknowledgements

This project was supported by TrustShare Innovation Chair. Akamai Technologies provided access to the hardware essential to our simulations. We would also like to thank Laurent Decreusefond, Emre Telatar, Nirupam Gupta and Anastasiia Kucherenko for fruitful discussions.

Cite As Get BibTex

João Paulo Bezerra, Veronika Anikina, Petr Kuznetsov, Liron Schiff, and Stefan Schmid. Dynamic Probabilistic Reliable Broadcast. In 28th International Conference on Principles of Distributed Systems (OPODIS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 324, pp. 31:1-31:30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/LIPIcs.OPODIS.2024.31

Abstract

Byzantine reliable broadcast is a fundamental primitive in distributed systems that allows a set of processes to agree on a message broadcast by a dedicated process, even when some of them are malicious (Byzantine). It guarantees that no two correct processes deliver different messages, and if a message is delivered by a correct process, every correct process eventually delivers one. Byzantine reliable broadcast protocols are known to scale poorly, as they require Ω(n²) message exchanges, where n is the number of system members. The quadratic cost can be explained by the inherent need for every process to relay a message to every other process.
In this paper, we explore ways to overcome this limitation by casting the problem to the probabilistic setting. We propose a solution in which every broadcast message is validated by a small set of witnesses, which allows us to maintain low latency and small communication complexity. In order to tolerate the slow adaptive adversary, we dynamically select the witnesses through a novel stream-local hash function: given a stream of inputs, it generates a stream of output hashed values that adapts to small deviations of the inputs.
Our performance analysis shows that the proposed solution exhibits significant scalability gains over state-of-the-art protocols.

Subject Classification

ACM Subject Classification
  • Theory of computation → Distributed algorithms
Keywords
  • Reliable broadcast
  • probabilistic algorithms
  • witness sets
  • stream-local hashing
  • cryptocurrencies
  • accountability

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Supplementary Materials

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