发表机构
Computer Science Department, University of Jaen; School of Computer Science and Electronic Engineering, University of Essex（贾恩大学计算机科学系; 埃塞克斯大学计算机科学与电子工程学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对区块链共识算法存在的问题，提出用直觉模糊集和幺模聚合运算研究验证者声誉行为的方法，能让验证者纠正过去失败，促进公平算法设计，保持线性计算复杂度，经实验验证可提升区块链网络公平性与包容性。
AI 中文摘要
区块链的运行由共识算法（CA）控制。一些共识机制需要大量计算能力，另一些则需要高额赌注来选择验证和核实区块中交易的参与者，导致权力集中和参与者被排除。本文提出一种新方法，通过使用直觉模糊集（IFS）和幺模聚合运算（UAO）研究验证者的声誉行为，来解决基于声誉的共识算法中的这些问题。我们的方法用IFS来表达“声誉”，因为共识算法中的声誉值最终意味着不确定性，IFS便于表示对声誉缺乏精确了解。此外，该方法利用幺模聚合运算来随时间监测声誉，并强化负面和正面声誉的重要性。因此，该解决方案允许验证者在后续验证过程中纠正过去的失败，并促进公平的共识算法设计。所提出的框架保持线性计算复杂度且不引入超出底层共识协议的额外通信开销。实验结果支持下，我们的方法展示了改进的性能和评估，有望在区块链网络公平性和包容性方面取得进展。
英文摘要
The operation of blockchain is governed by consensus algorithms (CA). Several consensus mechanisms require significant computational power, while others necessitate high amounts of stakes to select the participant to validate and verify the transactions in the block, leading to centralisation of power and participant exclusion. This paper proposes a novel methodology to address these issues in reputation-based consensus algorithms by studying the reputation behaviour of the validator using intuitionistic fuzzy sets (IFSs) and uninorm aggregation operations (UAOs). Our approach uses IFSs to express the "reputation" because the reputation values in a consensus algorithm eventually imply uncertainty, and IFSs facilitate the representation of a lack of precise knowledge about reputation. Moreover, this methodology utilises uninorm aggregation operations to monitor reputation over time and reinforces the importance of negative and positive reputation. Consequently, this solution allows validators to rectify past failures in subsequent verification processes and foster an equitable consensus algorithm design. The proposed framework maintains linear computational complexity and does not introduce additional communication overhead beyond the underlying consensus protocol. Supported by experimental results, our methodology demonstrates improved performance and evaluation, promising advancements in blockchain network fairness and inclusivity.
Journal refResults in Engineering (2026): 109943
DOI：10.1016/j.rineng.2026.109943
