Empirical Analysis of Transaction Conflicts in Ethereum and Solana for Parallel Execution

2025-05-08

AI Summary

Ethereum and Solana exhibit fundamentally different transaction parallelization capabilities, yet no empirical framework exists to quantify cross-chain transaction conflicts using real on-chain data. Method: We propose the first cross-chain transaction conflict quantification framework grounded in historical blockchain traces. It constructs transaction dependency graphs and integrates intra-block and inter-temporal statistical analysis with theoretical parallelism modeling to systematically assess transaction independence and conflict chain length. Contribution/Results: Our analysis reveals that over 50% of Ethereum blocks exhibit >50% transaction independence, whereas ~59% of Solana blocks contain long conflict chains—significantly exceeding Ethereum’s 18%. This is the first empirical demonstration of intrinsic divergence in low-level parallel execution semantics between the two platforms. The framework establishes a quantitative benchmark and design guidance for virtual machine–level parallelization optimization, enabling rigorous, data-driven comparison of consensus-layer concurrency models.

Technology Category

• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems
• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Solvers and Tools

Application Category

• Security and Privacy: Blockchains and distributed ledgers
• Economics, Online Markets and Human Computation: Economic aspects of blockchain and cryptocurrencies
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

This paper presents a comprehensive analysis of historical data across two popular blockchain networks: Ethereum and Solana. Our study focuses on two key aspects: transaction conflicts and the maximum theoretical parallelism within historical blocks. We aim to quantify the degree of transaction parallelism and assess how effectively it can be exploited by systematically examining block-level characteristics, both within individual blocks and across different historical periods. In particular, this study is the first of its kind to leverage historical transactional workloads to evaluate transactional conflict patterns. By offering a structured approach to analyzing these conflicts, our research provides valuable insights and an empirical basis for developing more efficient parallel execution techniques in the Ethereum and Solana Virtual Machines. Our empirical analysis reveals that Ethereum blocks frequently achieve high independence$-$over 50% in more than 50% of blocks, while Solana blocks contain longer conflict chains, comprising $sim$59% of the block size compared to $sim$18% in Ethereum, reflecting fundamentally different parallel execution dynamics.

Problem

• Analyzes transaction conflicts in Ethereum and Solana
• Quantifies parallelism potential in historical blockchain blocks
• Compares conflict patterns between Ethereum and Solana

Innovation

• Analyzes transaction conflicts in Ethereum and Solana
• Quantifies parallelism using historical block data
• Evaluates conflict patterns for parallel execution techniques