A Two-Stage PBFT Architecture With Trust and Reward Incentive Mechanism

被引:10
|
作者
Qushtom, Haytham [1 ]
Misic, Jelena [1 ]
Misic, Vojislav B. [1 ]
Chang, Xiaolin [2 ]
机构
[1] Toronto Metropolitan Univ, Dept Comp Sci, Toronto, ON M5B 2K3, Canada
[2] Beijing Jiaotong Univ, Beijing Key Lab Secur & Privacy Intelligent Transp, Beijing 100044, Peoples R China
基金
加拿大自然科学与工程研究理事会;
关键词
Blockchain; Internet of Things (IoT); practical Byzantine fault tolerance (PBFT); Proof of Stake (PoS);
D O I
10.1109/JIOT.2023.3243189
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The consensus algorithm is an essential ingredient of any blockchain system. Many different consensus mechanisms, such as practical Byzantine fault tolerance (PBFT), Proof-of-Work (PoW), Proof-of-Stake (PoS), and their many derivatives, have been proposed over the years, but the complementary problems of performance and resilience to malicious behavior of the nodes have yet to be resolved in a satisfactory manner. In this work, we propose a consensus mechanism that integrates PoS with PBFT, which can effectively deal with dishonest nodes, both individual validators and leaders, while maintaining high performance. Our model incentivized truthful behavior by using trust score and reward mechanisms as crucial components of the block validation and ordering processes. The performance of the proposed scheme is evaluated using an analytical model that employs a semi-Markov process, defined by an ergodic multidimensional Markov chain with a finite number of states. The results show the efficiency of the proposed model in consensus-based decision making, even under a high likelihood of dishonest node behavior.
引用
收藏
页码:11440 / 11452
页数:13
相关论文
共 50 条
  • [21] A two-stage incentive mechanism for rebalancing free-floating bike sharing systems: Considering user preference
    Wang, Junwei
    Wang, Yan
    TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2021, 82 : 54 - 69
  • [22] Deep Reinforcement Learning With a Stage Incentive Mechanism of Dense Reward for Robotic Trajectory Planning
    Peng, Gang
    Yang, Jin
    Li, Xinde
    Khyam, Mohammad Omar
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2023, 53 (06): : 3566 - 3573
  • [23] A Two-Stage ADC Architecture With VCO-Based Second Stage
    Gupta, A. K.
    Nagaraj, K.
    Viswanathan, T. R.
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2011, 58 (11) : 734 - 738
  • [24] A two-stage mechanism to improve electricity rationing
    Doucet, JA
    Min, KJ
    Roland, M
    Strauss, T
    CANADIAN JOURNAL OF ECONOMICS-REVUE CANADIENNE D ECONOMIQUE, 1996, 29 : S270 - S275
  • [25] Electricity rationing through a two-stage mechanism
    Doucet, JA
    Min, KJ
    Roland, M
    Strauss, T
    ENERGY ECONOMICS, 1996, 18 (03) : 247 - 263
  • [26] A Two-Stage Mechanism for Demand Response Markets
    Satchidanandan, Bharadwaj
    Roozbehani, Mardavij
    Dahleh, Munther A.
    IEEE CONTROL SYSTEMS LETTERS, 2022, 7 : 49 - 54
  • [27] Two-stage procedures for approximating the expected reward: The negative exponential case
    Jeng-Fu Liu
    Metrika, 1998, 48 : 223 - 230
  • [28] Two-stage procedures for approximating the expected reward: The negative exponential case
    Liu, JF
    METRIKA, 1998, 48 (03) : 223 - 230
  • [29] A Two-Stage Stackelberg Game Wind-Storage Planning Model Considering a Bus Carbon Intensity Incentive Mechanism
    Nan, Junpei
    Feng, Jieran
    Guan, Li
    Sun, Ke
    Deng, Xu
    Zhou, Hao
    APPLIED SCIENCES-BASEL, 2023, 13 (06):
  • [30] Study on reward incentive mechanism for companies' managers
    Liu, B
    Li, HM
    PROCEEDINGS OF 2003 INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE & ENGINEERING, VOLS I AND II, 2003, : 2515 - 2519