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AASC: Activity-Adjusted Stake Consensus for Scalable IoT Blockchains
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DOI：10.1145/3772290.3772307.png)
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Abstract
En 中文
Advances in decentralized decision-making have accelerated the adoption of the Internet of Things (IoT), with Blockchain emerging as a key distributed computing paradigm. It enables transparent multimodal data management without centralized infrastructure, ensuring traceability, trust, integrity, and authentication. Blockchain relies on consensus mechanisms validated by network participants, emphasizing the importance of fairness in these mechanisms, which is particularly critical for resource-constrained IoT systems with dynamically changing devices. To address this, we propose the Activity-Adjusted Stake Consensus (AASC) mechanism, a lightweight, iterative, and machine learning-augmented consensus protocol, specifically designed for Blockchain-enabled IoT. AASC continuously updates a reputation score (Consensus Score) for each IoT node, which reflects both historical and real-time node behaviors (activity), thereby enabling adaptive consensus even in a heterogeneous and ever-changing landscape. AASC is a novel approach that transcends conventional rule-based consensus, achieves remarkably low overhead with linear O(n) communication complexity and accessible O(n log n) computational complexity per node, making it efficient for resource-constrained environments. Extensive experiments and comparative analysis demonstrate that AASC outperforms leading lightweight consensus protocols in terms of fairness, security, and scalability. The architecture effectively manages node churn and mitigates Sybil, collusion, and monopolization attacks by directly integrating randomized validator selection and swift penalization into the activity-based trust system. Thus, AASC substantially improves the reliability and practicality of Blockchain in dynamic IoT networks, paving the way for widespread adoption.
Keywords:
Blockchain
Consensus Protocol
IoT
Fairness
Reputation
Activity
Trust
Security
Journal
P
PROCEEDINGS OF THE 27TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING AND NETWORKING, ICDCN 2026
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