Equity decentralized consensus algorithm based on incentive compatibility - Youliang TIAN; Yansen YUAN; Hongfeng GAO; Yang YANG; Jinbo XIONG (Tongxin xuebao)
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.