认证交易传播的带宽费用机制
Bandwidth Fee Mechanisms for Certified Transaction Dissemination
- University of Michigan（密歇根大学）
- Purdue University（普渡大学）
- Sei Labs（Sei实验室）
- University of Portsmouth（朴茨茅斯大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
研究共识前认证交易传播的带宽费用机制，提出贪心路由标价机制实现个体激励相容，并设计EIP-1559式价格更新规则保证稳定性。
AI中文摘要：
我们研究带宽费用机制（BFMs），用于在共识之前对阈值认证的交易传播进行定价。类似于计算中的交易费用机制，BFM为区块链通信定价，这在传播与共识和执行分离时尤其相关。我们将BFM建模为提交交易的用户与接收并转发交易的验证者之间的双边采购拍卖。任何验证者都可以充当交易的源，并将其转发给阈值数量的证明者。该模型考虑了从用户接收以及验证者之间的后续转移，同时抽象掉了不受限制的多跳八卦传播和网络拓扑。我们建立了短视激励相容性的限制：不存在非平凡的基于转录的BFM能够防止两个验证者之间的有利可图的合谋，并且不存在非平凡的BFM同时满足单个用户、单个验证者以及一个验证者与一个用户组成的联盟的激励相容性。在可行性方面，我们给出了一种贪心路由的标价机制，该机制对每个单独的用户和验证者都是激励相容的。我们还研究了跨区块的带宽定价。假设验证者诚实执行，我们提出了一种EIP-1559风格的价格更新规则，其流体近似具有唯一的不动点，该不动点在足够小的步长下是局部稳定的。在大市场中，从该点附近开始的价格在任意固定时间范围内以高概率保持在该点附近。
英文摘要：
We study bandwidth fee mechanisms (BFMs) for pricing threshold-certified transaction dissemination before consensus. Analogous to transaction fee mechanisms for computation, BFMs price blockchain communication, which is especially relevant when dissemination is separated from consensus and execution. We model BFMs as two-sided procurement auctions between users submitting transactions and validators receiving and forwarding them. Any validator may serve as a transaction's source and forward it to a threshold of attesters. The model accounts for receipt from the user and subsequent transfers between validators, while abstracting away unrestricted multi-hop gossip and network topology. We establish limits on myopic incentive compatibility: no nontrivial transcript-based BFM prevents profitable collusion between two validators, and no nontrivial BFM simultaneously satisfies incentive compatibility for individual users, individual validators, and coalitions of one validator and one user. On the feasibility side, we give a greedy-route posted-price mechanism that is incentive compatible for every individual user and validator. We also study bandwidth pricing across blocks. Assuming honest validator execution, we propose an EIP-1559-style price-update rule whose fluid approximation has a unique fixed point that is locally stable for sufficiently small step sizes. In large markets, prices starting near this point remain nearby with high probability over any fixed time horizon.
