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Robust and Fast Blockchain State Synchronization

Authors Enrique Fynn, Ethan Buchman, Zarko Milosevic, Robert Soulé, Fernando Pedone

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Author Details

Enrique Fynn
  • Università della Svizzera italiana (USI), Lugano, Switzerland
Ethan Buchman
  • Informal Systems, Guelph, Canada
Zarko Milosevic
  • Informal Systems, Guelph, Canada
Robert Soulé
  • Yale University, New Haven, CT, USA
Fernando Pedone
  • Università della Svizzera italiana (USI), Lugano, Switzerland

Funding

This work was supported in part by the Swiss National Science Foundation (grant 175717) and NSF FMitF (grant 2019285).

Cite As Get BibTex

Enrique Fynn, Ethan Buchman, Zarko Milosevic, Robert Soulé, and Fernando Pedone. Robust and Fast Blockchain State Synchronization. In 26th International Conference on Principles of Distributed Systems (OPODIS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 253, pp. 8:1-8:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023) https://doi.org/10.4230/LIPIcs.OPODIS.2022.8

Abstract

State synchronization, the process by which a new or recovering peer catches up with the state of other operational peers, is critical to the operation of blockchain-based systems. Existing approaches to state synchronization typically involve downloading snapshots of system state. Such approaches introduce an attack vector from malicious peers that can significantly degrade performance. Moreover, the process of creating snapshots leads to performance hiccups. This paper presents a technique for peers to catch up with operational peers without trusting any particular peer and gracefully recover from misbehavior during the process. We have integrated our design into a production blockchain middleware. Our evaluation shows that during operation, the transaction throughput is consistently higher without pauses for snapshot construction. Moreover, the time it takes for a new peer to join the blockchain is halved, while at the same time tolerating Byzantine peers.

Subject Classification

ACM Subject Classification
  • Computer systems organization → Reliability
  • Computer systems organization → Availability
  • Computer systems organization → Redundancy
  • Computing methodologies → Distributed algorithms
Keywords
  • state synchronization
  • replication
  • blockchain

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