@inbook{b0b6fed520d94d3d9e2c363f490cde2b,
title = "Optimality Despite Chaos in Fee Markets",
abstract = "Transaction fee markets are essential components of blockchain economies, as they resolve the inherent scarcity in the number of transactions that can be added to each block. In early blockchain protocols, this scarcity was resolved through a first-price auction in which users were forced to guess appropriate bids from recent blockchain data. Ethereum{\textquoteright}s EIP-1559 fee market reform streamlines this process through the use of a base fee that is increased (or decreased) whenever a block exceeds (or fails to meet) a specified target block size. Previous work has found that the EIP-1559 mechanism may lead to a base fee process that is inherently chaotic, in which case the base fee does not converge to a fixed point even under ideal conditions. However, the impact of this chaotic behavior on the fee market{\textquoteright}s main design goal – blocks whose long-term average size equals the target – has not previously been explored. As our main contribution, we derive near-optimal upper and lower bounds for the time-average block size in the EIP-1559 mechanism despite its possibly chaotic evolution. Our lower bound is equal to the target utilization level whereas our upper bound is ≈6% higher than optimal. Empirical evidence is shown in great agreement with these theoretical predictions. Specifically, the historical average was ≈2.9% larger than the target rage under Proof-of-Work and decreased to ≈2.0% after Ethereum{\textquoteright}s transition to Proof-of-Stake. We also find that an approximate version of EIP-1559 achieves optimality even in the absence of convergence.",
author = "Stefanos Leonardos and Dani{\"e}l Reijsbergen and Barnab{\'e} Monnot and Georgios Piliouras",
note = "Funding Information: This research is supported in part by the National Research Foundation, Singapore and DSO National Laboratories under its AI Singapore Program (AISG Award No: AISG2-RP-2020-016), NRF 2018 Fellowship NRF-NRFF2018-07, NRF2019-NRF-ANR095 ALIAS grant, grant PIESGP-AI-2020-01, AME Programmatic Fund (Grant No. A20H6b0151) from the Agency for Science, Technology and Research (A*STAR) and Provost{\textquoteright}s Chair Professorship grant with number RGEPPV2101. It is also supported by the National Research Foundation (NRF), Prime Minister{\textquoteright}s Office, Singapore, under its National Cybersecurity R&D Programme and administered by the National Satellite of Excellence in Design Science and Technology for Secure Critical Infrastructure, Award No. NSoE DeST-SCI2019-0009. Funding Information: Acknowledgements. This research is supported in part by the National Research Foundation, Singapore and DSO National Laboratories under its AI Singapore Program (AISG Award No: AISG2-RP-2020-016), NRF 2018 Fellowship NRF-NRFF2018-07, NRF2019-NRF-ANR095 ALIAS grant, grant PIESGP-AI-2020-01, AME Programmatic Fund (Grant No. A20H6b0151) from the Agency for Science, Technology and Research (A*STAR) and Provost{\textquoteright}s Chair Professorship grant with number RGEPPV2101. It is also supported by the National Research Foundation (NRF), Prime Minister{\textquoteright}s Office, Singapore, under its National Cybersecurity R&D Programme and administered by the National Satellite of Excellence in Design Science and Technology for Secure Critical Infrastructure, Award No. NSoE DeST-SCI2019-0009. Publisher Copyright: {\textcopyright} 2024, International Financial Cryptography Association.",
year = "2024",
doi = "10.1007/978-3-031-47751-5_20",
language = "English",
isbn = "9783031477508",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "346--362",
editor = "Foteini Baldimtsi and Christian Cachin",
booktitle = "Financial Cryptography and Data Security 2023",
}