Dynamic pricing model for Ethereum mempool stabilizes transaction scheduling

A new academic paper from researchers Fatemeh Fardno and S. Rasoul Etesami tackles a fundamental gap in Ethereum's transaction scheduling. While the existing EIP-1559 mechanism optimizes block pricing in a static snapshot, it ignores how transactions with heterogeneous sizes and per-unit values arrive over time, accumulate in the mempool, and compete for inclusion. The authors model this as a Markov Decision Process (MDP) where the state represents the full mempool configuration and actions are block prices. They first reinterpret static EIP-1559 as a primal-dual social-welfare optimization, showing block prices as dual variables. Then they extend to a dynamic framework that maximizes long-run discounted reward while incorporating holding costs and overshoot penalties.

The core contribution is applying a Natural Policy Gradient (NPG) algorithm to compute the optimal dynamic pricing policy. Results show that dynamic pricing stabilizes the mempool: as the overshoot penalty increases, the average scheduled transaction volume converges to the target block capacity. Moreover, the NPG updates closely resemble the EIP-1559 price update rule, suggesting a practical path to implementation. The paper also analyzes two special cases. For homogeneous transactions where the protocol directly controls scheduled volume, the optimal policy has a threshold structure. For uniform arrivals, they propose a bang-bang pricing mechanism and derive a lower bound on block capacity needed for system stability. This work bridges game theory, cryptography, and distributed systems, offering a rigorous foundation for next-generation Ethereum fee markets.