Herring: Parallel Batch-Order-Fairness on DAG-based Blockchain Consensus

2026-05-22

AI Summary

This work addresses fairness concerns in blockchain transaction ordering caused by Maximal Extractable Value (MEV) attacks, where existing batch-ordering fairness protocols suffer from poor performance and liveness vulnerabilities. The paper proposes a novel Byzantine Fault Tolerant (BFT) consensus protocol based on Directed Acyclic Graphs (DAGs), which, for the first time, achieves γ-batch-order-fairness within a DAG-based BFT framework under a multi-proposer architecture. By parallelizing the graph construction of the fairness layer and integrating post-consensus graph building, explicit resolution of missing edges, and a reliable broadcast coordination mechanism, the protocol is implemented in Rust as an extension of Narwhal & Tusk. Experimental results demonstrate that the system attains throughput close to native Narwhal & Tusk (approximately 10,000 tx/s), improves saturated throughput by 90% over FairDAG-RL and by 100% over DoD-W, significantly reduces execution latency, and eliminates the liveness flaws present in prior approaches.

Abstract

Transaction ordering attacks extract billions of dollars annually from decentralized finance users in the form of Maximal Extractable Value (MEV). Byzantine Fault-Tolerant (BFT) consensus protocols guarantee total order but place no constraint on how that order is chosen, leaving the door open for adversarial reordering. Batch-order-fairness (batch-OF) protocols close this gap, but existing designs pay a steep performance price for this guarantee. Leader-based protocols such as Themis concentrate all fairness decisions at a single replica, while recent DAG-based proposals FairDAG and DAG of DAGs (DoD) force their fairness layer into strictly serial execution despite running on multi-proposer DAGs. We present Herring, the first $γ$-batch-OF DAG BFT protocol whose fairness layer parallelizes the dominant graph construction cost across committed subdags. Herring combines post-consensus graph construction with explicit missing edge resolution piggybacked on the DAG's reliable broadcast layer, a pairing that turns fair ordering from a per-round serial bottleneck into a CPU-bound task. We also uncover previously unreported liveness vulnerabilities in both FairDAG-RL and DoD that a malicious client can trigger to halt the fairness layer indefinitely, and propose patches that we integrate into our reimplementations. We implement Herring on top of the Rust implementation of Narwhal \& Tusk and evaluate it against FairDAG-RL, DoD-W, and Themis. Herring tracks the throughput of Narwhal \& Tusk closely up to roughly $10{,}000$\,tx/s, achieves roughly $90\%$ higher saturation throughput than FairDAG-RL and $100\%$ higher than DoD-W, and substantially reduces execution latency at saturation.

Problem

• batch-order-fairness
• DAG-based blockchain
• Maximal Extractable Value
• Byzantine Fault-Tolerant consensus
• liveness vulnerability

Innovation

• batch-order-fairness
• DAG-based BFT
• parallel fairness
• MEV mitigation
• missing edge resolution