Areon: Latency-Friendly and Resilient Multi-Proposer Consensus

TL;DR

Areon introduces a novel multi-proposer proof-of-stake consensus protocol using a DAG structure, achieving latency-friendly, resilient, and robust finality even under partial synchrony and adversarial conditions.

Contribution

The paper presents Areon, a new DAG-based multi-proposer consensus protocol with formal properties and practical implementation, improving latency and robustness over traditional chain-based protocols.

Findings

Areon-Base achieves lower reorganization frequency and depth compared to Ouroboros Praos.

The protocol guarantees bounded-latency finality with high probability.

Experimental results show robustness under various network delays and adversarial stakes.

Abstract

We present Areon, a family of latency-friendly, stake-weighted, multi-proposer proof-of-stake consensus protocols. By allowing multiple proposers per slot and organizing blocks into a directed acyclic graph (DAG), Areon achieves robustness under partial synchrony. Blocks reference each other within a sliding window, forming maximal antichains that represent parallel ``votes'' on history. Conflicting subDAGs are resolved by a closest common ancestor (CCA)-local, window-filtered fork choice that compares the weight of each subDAG -- the number of recent short references -- and prefers the heavier one. Combined with a structural invariant we call Tip-Boundedness (TB), this yields a bounded-width frontier and allows honest work to aggregate quickly. We formalize an idealized protocol (Areon-Ideal) that abstracts away network delay and reference bounds, and a practical protocol (Areon-Base) that adds VRF-based eligibility, bounded short and long references, and application-level validity and conflict checks at the block level. On top of DAG analogues of the classical common-prefix, chain-growth, and chain-quality properties, we prove a backbone-style $(k,\varepsilon)$-finality theorem that calibrates confirmation depth as a function of the window length and target tail probability. We focus on consensus at the level of blocks; extending the framework to richer transaction selection, sampling, and redundancy policies is left to future work. Finally, we build a discrete-event simulator and compare Areon-Base against a chain-based baseline (Ouroboros Praos) under matched block-arrival rates. Across a wide range of adversarial stakes and network delays, Areon-Base achieves bounded-latency finality with consistently lower reorganization frequency and depth.