Design of reputation-driven blockchain sharding consensus and incentive mechanism

Abstract

The PBFT (Practical Byzantine Fault Tolerance) consensus algorithm was confronted with several challenges in the blockchain sharding environment, including high communication complexity, random leader election, node insecurity, and insufficient participation incentives. To address these issues, a reputation-driven blockchain sharding consensus and incentive mechanism was proposed. Reputation mechanisms were utilized to evaluate and incentivize node behavior, thereby enhancing system trust and promoting active participation. Aggregated signature technology was employed to merge consensus node signatures, and node voting weights were determined based on reputation assessments, which reduced communication overhead and improved consensus equality and security. Additionally, a deposit and incentive mechanism was introduced under reputation management, where initial entry standards were set and gradually increased over time according to reputation values. Differentiated incentive models, based on node roles, were designed to balance stable income and dynamic rewards, thereby continuously improving network stability and security. Simulation results demonstrated that the proposed R-PBFT consensus algorithm outperformed the traditional PBFT, maintaining lower latency and higher throughput, which effectively enhanced system performance. Furthermore, compared to proportional incentive allocation based solely on reputation, the proposed incentive mechanism achieves higher consensus participation rates.

Keywords

• blockchain
• sharding technique
• reputation
• PBFT consensus algorithm
• incentive