基于区块链和边缘辅助的CIoT身份解析框架

IF 9.9 2区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
IEEE Transactions on Consumer Electronics Pub Date : 2026-08-01 Epub Date: 2026-03-06 DOI:10.1109/TCE.2026.3671306
Jie Ji;Jian Shen;Pengfei Yue;Chen Wang;Haoyu Ma;Hao Lin
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引用次数: 0

摘要

在消费者物联网(CIoT)中,身份解析位于业务访问的关键路径上。传统的“链上背书,链下解决”模式仍然依赖于集中的入口点或一小部分固定节点。对于消费者设备,一旦此类入口点失败或受到攻击,解决方案中断和服务不可用就会直接被消费者感知到。为了解决这个问题,我们提出了一个区块链边缘协作身份解决框架(BECIR)。BECIR使用智能合约实现全生命周期链上标识符管理,并在没有中心节点的情况下提高一致性、抗篡改性和可追溯性。为了解决资源受限的消费者设备无法维持完整链上状态的问题,引入了边缘代理来承担全节点责任。我们进一步将设备边缘关联作为一个新的多目标优化问题,并在安全声誉、端到端延迟和负载平衡之间寻求帕累托最优权衡。此外,我们开发了一个基于全局异常指标的场景感知信誉模型,以动态表征节点风险。我们还提出了CAL-MOGWO,该算法通过质量感知的领导者选择、混沌摄动和自适应权重调整来改善探索-收敛平衡。大规模仿真结果表明,BECIR在复杂网络条件下保持低分辨率延迟和高并发性。与几种主流多目标算法相比,CAL-MOGWO具有更好的整体收敛性和解的分布质量。特别是相对于MOGWO, IGD减小了8.02%和63.65%,井距减小了61.05%和85.09%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BECIR: A Framework for Identity Resolution in the CIoT With Blockchain and Edge Assistance
In the Consumer Internet of Things (CIoT), identity resolution lies on the critical path of service access. The traditional paradigm of “on-chain endorsement, off-chain resolution” still depends on centralized entry points or a small set of fixed nodes. For consumer devices, once such entry points fail or are attacked, resolution interruption and service unavailability can become directly perceivable to consumers. To address this issue, we propose a Blockchain–Edge Collaborative Identity Resolution framework (BECIR). BECIR uses smart contracts to implement full-lifecycle on-chain identifier management and improves consistency, tamper resistance, and traceability without central nodes. To address the inability of resource-constrained consumer devices to maintain full on-chain state, edge proxies are introduced to undertake full-node responsibilities. We further formulate device–edge association as a new multi-objective optimization problem and seek Pareto-optimal trade-offs among security reputation, end-to-end latency, and load balancing. In addition, we develop a scenario-aware reputation model based on global anomaly indicators to characterize node risk dynamically. We also propose CAL-MOGWO, which improves the exploration–convergence balance through quality-aware leader selection, chaotic perturbation, and adaptive weight adjustment. Large-scale simulations show that BECIR maintains low resolution latency under complex network conditions and high concurrency. Compared with several mainstream multi-objective algorithms, CAL-MOGWO achieves better overall convergence and solution distribution quality. In particular, relative to MOGWO, IGD is reduced by 8.02% and 63.65%, and Spacing is reduced by 61.05% and 85.09%, respectively.
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来源期刊
CiteScore
7.70
自引率
9.30%
发文量
59
审稿时长
3.3 months
期刊介绍: The main focus for the IEEE Transactions on Consumer Electronics is the engineering and research aspects of the theory, design, construction, manufacture or end use of mass market electronics, systems, software and services for consumers.
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