The Blockchain Execution Dilemma: Optimizing Revenue XOR Fair Ordering

TL;DR

This paper presents a dynamic optimization framework for transaction sequencing in blockchains, balancing validator revenue and fairness, and demonstrates significant profit increases and congestion relief through a genetic algorithm.

Contribution

It introduces a blockchain-independent model for transaction scheduling and an anytime genetic algorithm to optimize validator revenue and fairness.

Findings

Validator profit increases by approximately 15% using the proposed algorithm.

Congestion relief is accelerated by up to 58%.

Strict fair ordering can reduce validator revenue by 50-60% during high congestion.

Abstract

The successive generations of consensus algorithms have progressively shifted the performance bottleneck of blockchains to the execution layer. While recent works address this by parallelizing transaction execution, they often overlook the critical role of transaction sequencing. Historically, transaction ordering was left to validator discretion, a practice prone to Maximal Extractable Value (MEV) attacks, or rigid fair-ordering protocols that limit validator revenue. In this work, we address the tension between validator revenue and order fairness using a dynamic optimization framework. We introduce a blockchain-independent model for transaction sequencing in a continuous setting where block executions can overlap. Within this framework, we propose an anytime genetic algorithm that utilizes gas prices, object sets, and predicted execution times to optimize schedules. We evaluate our approach with real-world datasets from Sui and Ethereum, and demonstrate that our algorithm increases validator profit by approximately 15% and accelerates congestion relief by up to 58%. Furthermore, we quantify the impact of fair-ordering constraints, showing they can reduce validator revenue by 50% to 60% during periods of high congestion. We provide the first evidence that enforcing strict fair ordering effectively nullifies the advantages of advanced sequencing.