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Probability Models of Distributed Proof Generation for zk-SNARK-Based Blockchains

Author

Listed:
  • Yuri Bespalov

    (Bogolyubov Institute for Theoretical Physics, 03143 Kiev, Ukraine)

  • Alberto Garoffolo

    (Horizen, 20121 Milan, Italy)

  • Lyudmila Kovalchuk

    (IOHK Research, Hong Kong)

  • Hanna Nelasa

    (Department of Information Security, Zaporizhzhia Polytechnic National University, 69063 Zaporizhzhia, Ukraine)

  • Roman Oliynykov

    (IOHK Research, Hong Kong)

Abstract

The paper is devoted to the investigation of the distributed proof generation process, which makes use of recursive zk-SNARKs. Such distributed proof generation, where recursive zk-SNARK-proofs are organized in perfect Mercle trees, was for the first time proposed in Latus consensus protocol for zk-SNARKs-based sidechains. We consider two models of a such proof generation process: the simplified one, where all proofs are independent (like one level of tree), and its natural generation, where proofs are organized in partially ordered set (poset), according to tree structure. Using discrete Markov chains for modeling of corresponding proof generation process, we obtained the recurrent formulas for the expectation and variance of the number of steps needed to generate a certain number of independent proofs by a given number of provers. We asymptotically represent the expectation as a function of the one variable n/m , where n is the number of provers m is the number of proofs (leaves of tree). Using results obtained, we give numerical recommendation about the number of transactions, which should be included in the current block, idepending on the network parameters, such as time slot duration, number of provers, time needed for proof generation, etc.

Suggested Citation

  • Yuri Bespalov & Alberto Garoffolo & Lyudmila Kovalchuk & Hanna Nelasa & Roman Oliynykov, 2021. "Probability Models of Distributed Proof Generation for zk-SNARK-Based Blockchains," Mathematics, MDPI, vol. 9(23), pages 1-31, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:23:p:3016-:d:687220
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    Citations

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    Cited by:

    1. Rico-Peña, Juan Jesús & Arguedas-Sanz, Raquel & López-Martin, Carmen, 2023. "Models used to characterise blockchain features. A systematic literature review and bibliometric analysis," Technovation, Elsevier, vol. 123(C).
    2. Xavier Salleras & Sergi Rovira & Vanesa Daza, 2022. "FORT: Right-Proving and Attribute-Blinding Self-Sovereign Authentication," Mathematics, MDPI, vol. 10(4), pages 1-18, February.

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