Empirical Analysis of Transaction Conflicts in Ethereum and Solana for Parallel Execution (2505.05358v2)

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 for smart contracts in the Ethereum and Solana virtual machines. Our empirical analysis reveals that historical Ethereum blocks frequently achieve high independence, over 50\% in more than 50\% of blocks, while Solana historical blocks contain longer conflict chains, comprising $\sim$59\% of the block size compared to $\sim$18\% in Ethereum, reflecting fundamentally different parallel execution dynamics.

• The paper quantifies transaction independence in Ethereum, showing over 50% independent transactions that boost potential throughput.
• It compares Ethereum's read-write oblivious model with Solana's read-write aware approach, highlighting stark differences in conflict dynamics.
• The study outlines actionable optimization strategies, including hybrid execution models and multi-version concurrency control, to enhance blockchain performance.

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

Introduction

The paper "Empirical Analysis of Transaction Conflicts in Ethereum and Solana for Parallel Execution" (2505.05358) provides a methodical investigation of transactional conflicts in blockchain networks, specifically focusing on Ethereum and Solana. The main objective is to quantify transaction parallelism and evaluate its effective application by exploring block-level dynamics. The distinct architectural choices of Ethereum and Solana regarding transaction execution paradigms form the basis of this comparative analysis.

Methodology

The analysis leverages historical data across both blockchain networks to investigate two primary aspects: transaction conflicts and the feasible degree of parallelism in historical blocks. With Ethereum employing a read-write oblivious model and Solana utilizing a read-write aware model, the paper disentangles the notable disparities in conflict dynamics between these two execution technologies. This analysis forms the empirical bedrock for improving parallel execution techniques tailored to the Ethereum and Solana Virtual Machines.

Findings

The findings highlight several critical insights into the transactional dynamics of both networks:

1. Ethereum's Transaction Independence:
   • Over 50% of Ethereum's historical blocks display more than 50% transaction independence. This independence increases the scope for parallel execution, offering a significant potential throughput boost under a parallel execution framework.
2. Solana's Longer Conflict Chains:
   • Solana blocks demonstrate a higher proportion of conflict chains, approximately 59% of the block size compared to Ethereum's 18%, indicating a denser interdependent transaction construction. This affects Solana's parallel execution capability, restricting the potential speedup due to these dependencies.

Conflict Analysis

Ethereum

1. Sequential Constraints:
   • The Ethereum Virtual Machine (EVM) processes transactions sequentially. The sequence is determined only during block execution, without prior knowledge of the read-write sets, requiring a strategy like optimistic execution for potential parallelism.
2. Directional Challenges:
   • The inherent sequential processing model results in substantial transaction conflicts, generally due to shared resource access among transactions interacting with smart contracts or externally owned accounts (EOAs).

Solana

1. Parallel Execution Enablement:
   • Solana's Sealevel execution engine capitalizes on user-declared read-write sets, facilitating a more informed transaction scheduling. This allows non-conflicting transactions to be executed concurrently, reducing execution times significantly compared to the EVM.
2. Conflict Identification:
   • Despite optimized parallelism, Solana's inherent architecture still suffers from dense transactional dependencies due to explicit state accesses, resulting in substantial conflict chains which remain a challenge for throughput maximization.

Practical Implications

The paper provides actionable insights beneficial for real-world blockchain deployment and optimization strategies:

1. Ethereum Execution Optimization:
   • Development of longer parallelizable transaction chains by reducing dependencies through strategic smart contract designs or deployment of optimistic concurrency controls with transactional memory.
2. Solana Conflict Reduction:
   • Adoption of techniques like multi-version concurrency control to alleviate the impact of write-write conflicts and enhance transaction throughput in high-conflict environments.

Future Work

Future research avenues include:

1. Hybrid Models:
   • Exploring adaptive or hybrid execution models for both Ethereum and Solana, balancing between read-write awareness and obliviousness to optimize conflict management without compromising scalability.
2. Resource Management Strategies:
   • Investigating resource distribution frameworks within nodes to handle peak loads effectively, ensuring consistency and reducing execution time across distributed networks.

Conclusion

This comprehensive empirical analysis elucidates the complex nature of transaction conflicts in prominent blockchain networks. By dissecting execution models and intrinsic transactional dynamics, the paper sets forth empirical foundations for improving blockchain performance through parallel execution techniques, equitable resource handling, and conflict management, paving the way for more efficient blockchain systems.