Taishan Scholars Program(tsqn202312231);The National Natural Science Foundation of China(62102209);The Natural Science Foundation of Shandong Provincial(ZR2024MF104);Shandong Provincial Key Research and Development Program(2021CXGC010107);The New 20 Project of Higher Education of Jinan, China(202228017)
TIAN H W, ZHANG S H, WANG L H, et al. Design of reputation-driven blockchain sharding consensus and incentive mechanism[J]. Chinese Journal of Network and Information Security, 2025, 11(1): 141-150.
TIAN H W, ZHANG S H, WANG L H, et al. Design of reputation-driven blockchain sharding consensus and incentive mechanism[J]. Chinese Journal of Network and Information Security, 2025, 11(1): 141-150. DOI: 10.11959/j.issn.2096-109x.2025002.
Design of reputation-driven blockchain sharding consensus and incentive mechanism
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.
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references
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