A user-oriented model for Oracles' Gas price prediction

被引:21
作者
Pierro, Giuseppe Antonio [1 ,2 ]
Rocha, Henrique [3 ]
Ducasse, Stephane [2 ]
Marchesi, Michele [1 ]
Tonelli, Roberto [1 ]
机构
[1] Univ Cagliari, Dipartimento Matemat & Informat, Cagliari, Italy
[2] Univ Lille, Inria, CNRS, Cent Lille,UMR 9189 CRISt, Lille, France
[3] Loyola Univ Maryland, Comp Sci Dept, Baltimore, MD USA
来源
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2022年 / 128卷
基金
英国科研创新办公室;
关键词
Ethereum; Gas; Transaction fees; Empirical study; Transaction pool; Gas price categories; BLOCKCHAIN;
D O I
10.1016/j.future.2021.09.021
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The Ethereum blockchain is a distributed database of transactions, where the Gas Oracles suggest the users the Gas price's categories to get a transaction recorded. The paper explores the idea that the Gas Oracles are based on a data-centered model which does not provide users with a reliable prediction. We present an empirical study to test the reliability of the existing Gas Oracles from both the points of view of the Gas price predictions and the existing categories. The study reveals that the Gas Oracles' predictions fail more often than advertised and shows that the Gas price categories do not correspond to the categories set by the users. Therefore we propose a user-oriented model for the Oracles' Gas price prediction, based on two Gas price categories actually corresponding to the users' interests and a new method to estimate the Gas price. The new method, performing the Poisson regression at smaller intervals of time, predicts the Gas price to pay with a lower margin of error when compared to the actual one. The predictions based on the user-oriented model thus provide the users with a more effective Gas price to set. (c) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页码:142 / 157
页数:16
相关论文
共 35 条
  • [1] AA.VV, 2020, **DATA OBJECT**, DOI [10.5281/zenodo.3758103, DOI 10.5281/ZENODO.3758103]
  • [2] Why do businesses go crypto? An empirical analysis of initial coin offerings
    Adhami, Saman
    Giudici, Giancarlo
    Martinazzi, Stefano
    [J]. JOURNAL OF ECONOMICS AND BUSINESS, 2018, 100 : 64 - 75
  • [3] Blockchain Competition Between Miners: A Game Theoretic Perspective
    Altman, Eitan
    Menasche, Daniel
    Reiffers-Masson, Alexandre
    Datar, Mandar
    Dhamal, Swapnil
    Touati, Corinne
    El-Azouzi, Rachid
    [J]. FRONTIERS IN BLOCKCHAIN, 2020, 2
  • [4] Buterin V., 2014, CISC VIS NETW IND GL, V3, P36, DOI DOI 10.5663/APS.V1I1.10138
  • [5] Understanding Ethereum via Graph Analysis
    Chen, Ting
    Li, Zihao
    Zhu, Yuxiao
    Chen, Jiachi
    Luo, Xiapu
    Lui, John Chi-Shing
    Lin, Xiaodong
    Zhang, Xiaosong
    [J]. ACM TRANSACTIONS ON INTERNET TECHNOLOGY, 2020, 20 (02)
  • [6] Chen T, 2017, 2017 IEEE 24TH INTERNATIONAL CONFERENCE ON SOFTWARE ANALYSIS, EVOLUTION, AND REENGINEERING (SANER), P442, DOI 10.1109/SANER.2017.7884650
  • [7] The Analysis of Count Data: A Gentle Introduction to Poisson Regression and Its Alternatives
    Coxe, Stefany
    West, Stephen G.
    Aiken, Leona S.
    [J]. JOURNAL OF PERSONALITY ASSESSMENT, 2009, 91 (02) : 121 - 136
  • [8] Information Propagation in the Bitcoin Network
    Decker, Christian
    Wattenhofert, Roger
    [J]. 13TH IEEE INTERNATIONAL CONFERENCE ON PEER-TO-PEER COMPUTING (P2P), 2013,
  • [9] Ducasse S., 2019, BLOCKCHAIN WEB 3 0 S
  • [10] Scenario-based creation and digital investigation of ethereum ERC20 tokens
    Dyson, Simon F.
    Buchanan, William J.
    Bell, Liam
    [J]. FORENSIC SCIENCE INTERNATIONAL-DIGITAL INVESTIGATION, 2020, 32 (32):