Table of Contents
Fetching ...

Validated Strong Consensus Protocol for Asynchronous Vote-based Blockchains

Yibin Xu, Jianhua Shao, Tijs Slaats, Boris Düdder, Yongluan Zhou

TL;DR

The paper tackles liveness in asynchronous, vote-based blockchains by introducing Validated Strong BFT, a consensus model that permits leader-based proposals without requiring immediate agreement among honest nodes. It defines a multi-input, single-output consensus mechanism where blocks compete in voting rounds and mutually exclusive branches are gradually pruned via vote graphs, with safety guarantees enforced by compliant voting and a structured acceptance condition. Liveness is achieved through randomness from network delays and, when needed, a strong common coin, enabling the system to converge to a single accepted block despite Byzantine leaders or asynchronous delays. The proposed protocol reduces message and data costs to near-linear scales, supports nested concurrent consensus instances, and demonstrates competitive performance in both good- and bad-case latency scenarios, outperforming ACS-based approaches in large-scale, asynchronous networks. Overall, the approach offers a practical, scalable path to asynchronous, vote-based blockchains with robust fault tolerance and efficient consensus progression.

Abstract

Vote-based blockchains construct a state machine replication (SMR) system among participating nodes, using Byzantine Fault Tolerance (BFT) consensus protocols to transition from one state to another. Currently, they rely on either synchronous or partially synchronous networks with leader-based coordination or costly Asynchronous Common Subset (ACS) protocols in asynchronous settings, making them impractical for large-scale asynchronous applications. To make Asynchronous SMR scalable, this paper proposes a \emph{validated strong} BFT consensus model that allows leader-based coordination in asynchronous settings. Our BFT consensus model offers the same level of tolerance as binary byzantine agreement but does not demand consistency among honest nodes before they vote. An SMR using our model allows nodes to operate in different, tentative, but mutually exclusive states until they eventually converge on the same state. We propose an asynchronous BFT protocol for vote-based blockchains employing our consensus model to address several critical challenges: how to ensure that nodes eventually converge on the same state across voting rounds, how to assure that a blockchain will steadily progress through epochs while reaching consensus for previous epochs, and how to maintain robust byzantine fault tolerance. Our protocol greatly reduces message complexity and is the first one to achieve linear view changes without relying on threshold signatures. We prove that an asynchronous blockchain built on our protocol can operate with the \emph{same} simplicity and efficiency as partially synchronous blockchains built on, e.g. HotStuff-2. This facilitates deploying asynchronous blockchains across large-scale networks.

Validated Strong Consensus Protocol for Asynchronous Vote-based Blockchains

TL;DR

The paper tackles liveness in asynchronous, vote-based blockchains by introducing Validated Strong BFT, a consensus model that permits leader-based proposals without requiring immediate agreement among honest nodes. It defines a multi-input, single-output consensus mechanism where blocks compete in voting rounds and mutually exclusive branches are gradually pruned via vote graphs, with safety guarantees enforced by compliant voting and a structured acceptance condition. Liveness is achieved through randomness from network delays and, when needed, a strong common coin, enabling the system to converge to a single accepted block despite Byzantine leaders or asynchronous delays. The proposed protocol reduces message and data costs to near-linear scales, supports nested concurrent consensus instances, and demonstrates competitive performance in both good- and bad-case latency scenarios, outperforming ACS-based approaches in large-scale, asynchronous networks. Overall, the approach offers a practical, scalable path to asynchronous, vote-based blockchains with robust fault tolerance and efficient consensus progression.

Abstract

Vote-based blockchains construct a state machine replication (SMR) system among participating nodes, using Byzantine Fault Tolerance (BFT) consensus protocols to transition from one state to another. Currently, they rely on either synchronous or partially synchronous networks with leader-based coordination or costly Asynchronous Common Subset (ACS) protocols in asynchronous settings, making them impractical for large-scale asynchronous applications. To make Asynchronous SMR scalable, this paper proposes a \emph{validated strong} BFT consensus model that allows leader-based coordination in asynchronous settings. Our BFT consensus model offers the same level of tolerance as binary byzantine agreement but does not demand consistency among honest nodes before they vote. An SMR using our model allows nodes to operate in different, tentative, but mutually exclusive states until they eventually converge on the same state. We propose an asynchronous BFT protocol for vote-based blockchains employing our consensus model to address several critical challenges: how to ensure that nodes eventually converge on the same state across voting rounds, how to assure that a blockchain will steadily progress through epochs while reaching consensus for previous epochs, and how to maintain robust byzantine fault tolerance. Our protocol greatly reduces message complexity and is the first one to achieve linear view changes without relying on threshold signatures. We prove that an asynchronous blockchain built on our protocol can operate with the \emph{same} simplicity and efficiency as partially synchronous blockchains built on, e.g. HotStuff-2. This facilitates deploying asynchronous blockchains across large-scale networks.
Paper Structure (49 sections, 8 equations, 14 figures, 4 tables, 3 algorithms)

This paper contains 49 sections, 8 equations, 14 figures, 4 tables, 3 algorithms.

Figures (14)

  • Figure 1: An example of consensus chain propagation: Node 1 generated Block 1, stemming from Block 0. Block 2 did not extend Block 1; instead, it extended Block 0. Block 3 extended Block 1, etc. This figure also illustrates the vote view $\operatorname{VV}_j^{(k)}$ and the vote count $\operatorname{VC}_j^{(k)}$, for $k=3$. The numbers in the blue and red circles on Block X are $\operatorname{VV}_j^{(3)}[X]$ and $\operatorname{VC}_j^{(3)}[X]$ respectively. $G_j^{(3)}$ contains votes until height 2 to the knowledge of node $j$.
  • Figure 2: A visualization of $G_4^{(5)}$
  • Figure 3: The example showing the process of updating $cph$
  • Figure 4: The vote size and the data required for storing all votes at a block height with $p=10^{-7}$ and different $N$
  • Figure 5: Experiment Results for shorter block interval (100 epochs with 1000 transactions emitted every 5 secs).
  • ...and 9 more figures