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Step on the Gas? A Better Approach for Recommending the Ethereum Gas Price

In: Mathematical Research for Blockchain Economy

Author

Listed:
  • Sam M. Werner

    (Imperial College London)

  • Paul J. Pritz

    (Imperial College London)

  • Daniel Perez

    (Imperial College London)

Abstract

In the Ethereum network, miners are incentivized to include transactions in a block depending on the gas price specified by the sender. The sender of a transaction therefore faces a trade-off between timely inclusion and cost of his transaction. Existing recommendation mechanisms aggregate recent gas price data on a per-block basis to suggest a gas price. We perform an empirical analysis of historic block data to motivate the use of a predictive model for gas price recommendation. Subsequently, we propose a novel mechanism that combines a deep-learning based price forecasting model as well as an algorithm parameterized by a user-specific urgency value to recommend gas prices. In a comprehensive evaluation on real-world data, we show that our approach results on average in costs savings of more than 50% while only incurring an inclusion delay of 1.3 blocks, when compared to the gas price recommendation mechanism of the most widely used Ethereum client.

Suggested Citation

  • Sam M. Werner & Paul J. Pritz & Daniel Perez, 2020. "Step on the Gas? A Better Approach for Recommending the Ethereum Gas Price," Springer Proceedings in Business and Economics, in: Panos Pardalos & Ilias Kotsireas & Yike Guo & William Knottenbelt (ed.), Mathematical Research for Blockchain Economy, pages 161-177, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-53356-4_10
    DOI: 10.1007/978-3-030-53356-4_10
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    Citations

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    Cited by:

    1. Conall Butler & Martin Crane, 2023. "Blockchain Transaction Fee Forecasting: A Comparison of Machine Learning Methods," Mathematics, MDPI, vol. 11(9), pages 1-26, May.
    2. Sam M. Werner & Daniel Perez & Lewis Gudgeon & Ariah Klages-Mundt & Dominik Harz & William J. Knottenbelt, 2021. "SoK: Decentralized Finance (DeFi)," Papers 2101.08778, arXiv.org, revised Sep 2022.
    3. Daniel Perez & Sam M. Werner & Jiahua Xu & Benjamin Livshits, 2020. "Liquidations: DeFi on a Knife-edge," Papers 2009.13235, arXiv.org, revised Dec 2021.
    4. Lennart Ante & Aman Saggu, 2024. "Time-Varying Bidirectional Causal Relationships between Transaction Fees and Economic Activity of Subsystems Utilizing the Ethereum Blockchain Network," JRFM, MDPI, vol. 17(1), pages 1-28, January.

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