Abstract:In leader-based State Machine Replication (SMR), the leader's outgoing bandwidth is a natural throughput bottleneck. Erasure coding can alleviate this by letting the leader send each processor one fragment of each block rather than a full copy. The data expansion rate, the ratio of total data sent to payload size, determines how close throughput can get to network bandwidth.
We investigate the fundamental limits of bandwidth-efficient leader-based consensus. We prove that protocols with 2-round finality (one voting round) cannot achieve a data expansion rate below approximately~$2.5$, matching existing protocols. Protocols with 3-round finality (two voting rounds) can do significantly better: the second voting round provides a recovery mechanism, letting leaders attempt aggressive erasure codes and safely fall back to conservative ones when reconstruction fails, without compromising consistency.
We present two 3-round protocols realising this. Carnot~1 solves Extractable SMR, in which any correct processor can efficiently reconstruct any finalised block from fragments held by correct processors, but processors need not hold full blocks locally; this suffices for settings such as data availability layers. Carnot~1 assumes $n \geq 4f+1$ (at most $f$ Byzantine) and requires no fragment dissemination beyond the initial messages. Carnot~2 solves full SMR, where every correct processor eventually receives every finalised transaction. It operates under optimal resilience $n \geq 3f+1$, at the cost of additional fragment dissemination when Byzantine processors interfere. Both protocols support stable leaders. Under favourable conditions, leaders can use expansion rates approaching $1$; under adversarial conditions, they revert to safe rates of approximately $1.33$ and $1.5$, respectively, both well below the $2.5$ lower bound for 2-round finality.
From: Andrew Lewis-Pye [view email]
[v1]
Thu, 12 Mar 2026 10:59:35 UTC (48 KB)
[v2]
Sun, 31 May 2026 16:27:59 UTC (82 KB)
[v3]
Tue, 28 Jul 2026 07:56:19 UTC (84 KB)
此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。