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Analyzing Reward Dynamics and Decentralization in Ethereum 2.0: An Advanced Data Engineering Workflow and Comprehensive Datasets for Proof-of-Stake Incentives (2402.11170v1)

Published 17 Feb 2024 in econ.GN, cs.CR, cs.CY, cs.DB, cs.DC, and q-fin.EC

Abstract: Ethereum 2.0, as the preeminent smart contract blockchain platform, guarantees the precise execution of applications without third-party intervention. At its core, this system leverages the Proof-of-Stake (PoS) consensus mechanism, which utilizes a stochastic process to select validators for block proposal and validation, consequently rewarding them for their contributions. However, the implementation of blockchain technology often diverges from its central tenet of decentralized consensus, presenting significant analytical challenges. Our study collects consensus reward data from the Ethereum Beacon chain and conducts a comprehensive analysis of reward distribution and evolution, categorizing them into attestation, proposer and sync committee rewards. To evaluate the degree of decentralization in PoS Ethereum, we apply several inequality indices, including the Shannon entropy, the Gini Index, the Nakamoto Coefficient, and the Herfindahl-Hirschman Index (HHI). Our comprehensive dataset is publicly available on Harvard Dataverse, and our analytical methodologies are accessible via GitHub, promoting open-access research. Additionally, we provide insights on utilizing our data for future investigations focused on assessing, augmenting, and refining the decentralization, security, and efficiency of blockchain systems.

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References (33)
  1. L.Zhang & Zhang, F. Understand waiting time in transaction fee mechanism: An interdisciplinary perspective, https://doi.org/10.48550/arXiv.2305.02552 (2023). 2305.02552.
  2. Shaping the future of ethereum: Exploring energy consumption in proof-of-work and proof-of-stake consensus. \JournalTitleFrontiers in Blockchain 6 (2023).
  3. Reward distribution in proof-of-stake protocols: A trade-off between inclusion and fairness. \JournalTitleIEEE Access 11, 134136–134145 (2023).
  4. Characterizing wealth inequality in cryptocurrencies. \JournalTitleFrontiers in Blockchain (2021).
  5. Sok: A stratified approach to blockchain decentralization. \JournalTitlearXiv preprint arXiv:2211.01291 (2022).
  6. Sok: Blockchain decentralization, https://doi.org/10.48550/arXiv.2205.04256 (2023). 2205.04256.
  7. Is decentralized finance actually decentralized? a social network analysis of the aave protocol on the ethereum blockchain, https://doi.org/10.48550/arXiv.2206.08401 (2023). 2206.08401.
  8. Blockchain network analysis: A comparative study ofdecentralized banks. In Arai, K. (ed.) Intelligent Computing, 1022–1042, https://doi.org/10.1007/978-3-031-37717-4_67 (Springer Nature Switzerland, Cham, 2023).
  9. Xiao, Y. et al. “centralized or decentralized?”: Concerns and value judgments of stakeholders in the non-fungible tokens (nfts) market, 10.31219/osf.io/evz4p (2023).
  10. Zhang, L. The future of finance: Synthesizing cefi and defi for the benefit of all. In Miciuła, D. I. (ed.) Financial Literacy in Today´s Global Market, chap. 0, https://doi.org/10.5772/intechopen.1003042 (IntechOpen, Rijeka, 2023).
  11. A coefficient of variation method to measure the extents of decentralization for bitcoin and ethereum networks. \JournalTitleInternational Journal of Network Security (2020).
  12. Liu, Y. et al. Empirical analysis of eip-1559: Transaction fees, waiting times, and consensus security. In Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2099–2113 (2022).
  13. Ai ethics on blockchain: Topic analysis on twitter data for blockchain security. In Arai, K. (ed.) Intelligent Computing, 82–100, https://doi.org/10.1007/978-3-031-37963-5_7 (Springer Nature Switzerland, Cham, 2023).
  14. Li, Z. et al. Demystifying defi mev activities in flashbots bundle. In Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 165–179 (2023).
  15. Replication Data for: “Analyzing Reward Dynamics and Decentralization in Ethereum 2.0: An Advanced Data Engineering Workflow and Comprehensive Datasets for Proof-of-Stake Incentives”, 10.7910/DVN/OKQRS1 (2024).
  16. Zhang, L. Machine learning for blockchain: Literature review and open research questions. In NeurIPS 2023 AI for Science Workshop (2023).
  17. e-pos: Making proof-of-stake decentralized and fair. \JournalTitleIEEE Transactions on Parallel and Distributed Systems 32, 1961–1973 (2021).
  18. Uniswap daily transaction indices by network. \JournalTitlearXiv preprint arXiv:2312.02660 (2023). Accepted as a poster and presented at the Crypto Finance Conference St. Moritz Academic Research Track (CfC-SMART24). Suvretta House, St. Moritz, Switzerland. Jan. 12, 2024.
  19. An event study of the ethereum transition to proof-of-stake. \JournalTitleCommodities 2, 96–110 (2023).
  20. Centralization in block building and proposer-builder separation. \JournalTitlearXiv preprint arXiv:2401.12120 (2024).
  21. Staking pools on blockchains. \JournalTitlearXiv preprint arXiv:2203.05838 (2022).
  22. Pool competition and centralization in pos blockchain network. \JournalTitleApplied Economics 1–20 (2023).
  23. Staking pool centralization in proof-of-stake blockchain network. \JournalTitleAvailable at SSRN 3609817 (2020).
  24. Dynamical analysis of the eip-1559 ethereum fee market. In Proceedings of the 3rd ACM Conference on Advances in Financial Technologies, 114–126 (2021).
  25. Exploiting ethereum after “the merge”: The interplay between pos and mev strategies. In Proceedings of the Italian Conference on Cybersecurity (ITASEC 2023) (2023).
  26. Inflation and cryptocurrencies revisited: A time-scale analysis. \JournalTitleEconomics Letters 206, 109996 (2021).
  27. Educational game on cryptocurrency investment: Using microeconomic decision-making to understand macroeconomics principles. \JournalTitleEastern Economic Journal 49, 262–272, https://doi.org/10.1057/s41302-023-00240-7 (2023).
  28. Bitcoin gold, litecoin silver:an introduction to cryptocurrency’s valuation and trading strategy, https://doi.org/10.48550/arXiv.2308.00013 (2023). 2308.00013.
  29. On the mechanics of nft valuation: Ai ethics and social media, https://doi.org/10.31219/osf.io/qwpdx (2023).
  30. A data science pipeline for algorithmic trading: A comparative study of applications for finance and cryptoeconomics. In 2022 IEEE International Conference on Blockchain (Blockchain), 298–303, https://doi.org/10.1109/Blockchain55522.2022.00048 (2022).
  31. Liu, Y. & L.Zhang. Cryptocurrency valuation: An explainable ai approach. In Arai, K. (ed.) Intelligent Computing, 785–807, https://doi.org/10.1007/978-3-031-37717-4_51 (Springer Nature Switzerland, Cham, 2023).
  32. Augusto, A. et al. Sok: Security and privacy of blockchain interoperability. \JournalTitleAuthorea Preprints 10.36227/techrxiv.24595764.v1 (2023).
  33. A survey on blockchain interoperability: Past, present, and future trends. \JournalTitleACM Computing Surveys (CSUR) 54, 1–41 (2021).
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