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

Published 8 May 2025 in cs.DC and cs.ET

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.

Summary

Analysis of Transaction Conflicts in Ethereum and Solana for Parallel Execution

The paper "Empirical Analysis of Transaction Conflicts in Ethereum and Solana for Parallel Execution" offers an extensive examination of transactional conflicts within the Ethereum and Solana blockchain networks, with a focus on identifying potential for parallel execution. The paper leverages historical data to quantify transaction independence and conflicts, providing insights into how these characteristics affect the efficiency of blockchain virtual machines (VMs). By analyzing the execution dynamics within these leading blockchain platforms, the research presents a comparative view of execution strategies and conflict paradigms, which are central to optimizing throughput and scalability.

Key Findings and Methodology

The research rigorously investigates transactions processed by Ethereum and Solana, two blockchain networks with notably different architectures and transaction execution models: Ethereum employs a read-write oblivious execution model, while Solana utilizes a read-write aware model. The objective is to explore and quantify transaction conflicts and assess parallelism levels within historical blocks.

  1. Ethereum's Transaction Characteristics:
    • Ethereum processes transactions sequentially and lacks prior information about transactional state accesses. As a result, conflicts are identified during execution, leading to potential inefficiencies in throughput. The paper reveals that over 50% of Ethereum blocks provide more than 50% transaction independence, suggesting significant unexplored parallelism.
    • The analysis identifies that the longest chains of conflicting transactions comprise about 16-17% of typical Ethereum blocks, indicating that even with perfect parallel execution, a segment of transactions must remain sequential due to inherent dependencies.
  2. Solana's Transaction Characteristics:
    • Solana's execution model requires upfront knowledge of state read-write sets, enabling parallel execution with reduced conflicts. However, the paper highlights that Solana still contains significant conflict chains, with 93-100% of transactions deemed conflicting in certain historical periods.
    • Write-write conflicts dominate in Solana, accounting for a substantial portion of transaction contention. Despite Solana's architecture optimizing for speed, the presence and density of conflict chains constrain achievable parallelism and necessitate effective congestion management strategies.

Comparative Insights and Implications

The paper juxtaposes Ethereum's and Solana's approaches to execution and conflict management, drawing conclusions that highlight distinctive design trade-offs:

  • Parallel Execution Potential Versus Conflict Rate:
    • Ethereum's optimistic execution is constrained by dynamically identified conflicts, with potential gains if speculative execution failures can be minimized through improved conflict prediction. The paper suggests Ethereum can significantly benefit from frameworks capable of improving transaction parallelization by leveraging insights into conflict distributions.
    • Solana, while structured to support high throughput through concurrent execution, faces diminished transaction success rates due to its execution model's limitations in handling high-conflict environments. Adaptive techniques may help in mitigating failure rates by managing write-write conflicts more adeptly.
  • Impacts on Blockchain Scalability:
    • Enhancements in execution strategy, including hybrid models that combine dynamic and static conflict identification, could provide both networks with avenues to boost transaction throughput. Blockchain platforms can leverage findings from this analysis to refine their transaction scheduling and execution strategies, potentially achieving substantial improvements in resource utilization and processing capacity.

Future Directions

This research opens the door to multiple future investigations aimed at evolving blockchain execution environments. Developing adaptive or hybrid execution models capable of dynamically aligning with transaction-specific conflict patterns could emerge as a key area of development. Additionally, exploring the empirical application of multi-version data structures or advanced concurrency control mechanisms may deliver tangible enhancements in network throughput, thereby further cementing the applicability of blockchain technology in high-demand scenarios.

In conclusion, the authors demonstrate that while both Ethereum and Solana have untapped potential for parallel execution, challenges remain that require developments in conflict management and scheduling strategies. This paper crucially underpins the relationship between transaction conflicts and execution efficiency, contributing essential knowledge to the continued evolution of blockchain technology.

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