Journal on Communications ›› 2022, Vol. 43 ›› Issue (12): 101-112.doi: 10.11959/j.issn.1000-436x.2022232

• Papers • Previous Articles     Next Articles

Equity decentralized consensus algorithm based on incentive compatibility

Youliang TIAN1,2,3,4, Yansen YUAN1,2,3,4, Hongfeng GAO2,3,4, Yang YANG5, Jinbo XIONG6   

  1. 1 State Key Laboratory of Public Big Data, Guizhou University, Guiyang 550025, China
    2 College of Computer Science and Technology, Guizhou University, Guiyang 550025, China
    3 Institute of Cryptography &Date Security, Guizhou University, Guiyang 550025, China
    4 Guizhou Province Key Laboratory of Cryptography and Block Chain Technology, Guizhou University, Guiyang 550025, China
    5 School of Computing and Information Systems, Singapore Management University, Singapore 188065, Singapore
    6 College of Computer and Cyber Security, Fujian Normal University, Fuzhou 350117, China
  • Revised:2022-11-08 Online:2022-12-25 Published:2022-12-01
  • Supported by:
    The National Key Research and Development Program of China(2021YFB3101100);Key Program of the National Natural Science Union Foundation of China(U1836205);Project of High-level Innovative Talents of Guizhou Province([2020]6008);Science and Technology Program of Guiyang([2021]1-5);Science and Technology Program of Guiyang([2022]2-4);Science and Technology Program of Guizhou Province([2020]5017);Science and Technology Program of Guizhou Province([2022]065)

Abstract:

The PoW consensus algorithm has been proved to be incentive incompatible, existing computing centralization under high reward differences and slow convergence of forks in extreme cases.Based on this, an incentive-compatiblebased consensus algorithm SSPoW was proposed.By introducing local solutions to calculate the computing power aggregated on the block chain, the explicit quantification of computing power was used to speed up the convergence of the fork, thus satisfying the consistency of the blockchain.Incentive compatibility was achieved by improving the reward scheme, which reduced the problem of computing centralization caused by high reward differences.Simulation results prove that the proposed algorithm could effectively reduce the reward differences and is more efficient than the traditional PoW consensus algorithm, which has positive implications for improving system security and consensus efficiency.

Key words: consensus algorithm, cooperative mining, fork convergence, rewarding scheme

CLC Number: 

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