Modern blockchains increasingly rely on parallel execution to improve throughput. We show several industry and academic transaction fee mechanisms (TFMs) struggle to simultaneously account for execution parallelism while remaining performant and fair. First, if parallelism affects fees, adversarial protocol manipulations that offset possible benefits to throughput by introducing fake transactions become rational: users can insert functionally useless parallel transactions solely to reduce fees, and schedulers can create useless sequential transactions to increase revenue. Execution contingency, a core feature of expressive programming languages, both exacerbates the aforementioned threats and introduces new ones: (1) users may overpay for unused resources, and (2) scheduler revenue is harmed when reserved scheduling slots go unused due to contingency. We introduce a framework for this challenging setting, and prove an impossibility, highlighting an inherent tension: both parallelism and contingency involve a trade-off between minimizing risks for users and schedulers, as favoring one comes at the expense of the other. To complete the picture, we introduce a fee mechanisms and prove that they achieve the boundaries of this trade-off. Our results provide rigorous foundations for evaluating designs advanced by notable blockchains, such as Sui and Monad.

翻译：现代区块链日益依赖并行执行来提升吞吐量。我们证明，若干产业界与学术界的交易费用机制难以在保持高性能和公平性的同时，妥善应对执行并行性。首先，若并行性影响费用，智能合约协议操纵者就会产生理性动机——通过引入虚假交易抵消并行执行的吞吐量提升收益：用户可仅出于降低费用的目的插入功能无效的并行交易，调度者则能创建无效的串行交易以增加收益。执行不确定性作为可表达性编程语言的核心特性，既加剧了上述威胁，又引入了新型风险：（1）用户可能为未使用的资源过度付费；（2）当保留的调度时隙因不确定性未被占用时，调度者收益将受损。我们针对这一挑战性场景提出分析框架，并证明一个不可能性定理，揭示了内在的权衡困境：并行性与不确定性均涉及用户与调度者之间的风险最小化取舍，任何一方的优化都将以牺牲另一方为代价。为完善理论图景，我们设计了一种费用机制，并证明其能实现此类权衡的边界条件。我们的研究结果为评估Sui、Monad等知名区块链所推行的设计方案提供了严谨的理论基础。