Reputation and Energy-Aware Dynamic Hybrid Consensus (READ-HC) Model for IIoT

Industry 4.0, the fourth industrial revolution, advances (Industrial IoT) IIoT with autonomous, adaptive systems capable of self-learning and self-healing. Blockchain technology offers a decentralised, safe, and auditable framework to exchange and authenticate data through transactions without relying on third parties. Private blockchains, with flexible rules and strong privacy, could therefore be deployed inside IIoT systems to address security concerns and process large volumes of data. Traditional consensus mechanisms in blockchain, such as PoW and PoS, are computationally demanding and energy-intensive and may not be suitable for resource-constrained IIoT scenarios. Centralised architectures are also vulnerable in terms of single-point failures. Therefore, this article introduces a novel blockchain-based approach, Reputation and Energy-Aware Dynamic Hybrid Consensus (READ-HC), that integrates Practical Byzantine Fault Tolerance, Proof of Reputation for emphasising reliable nodes, and an energy-efficient mechanism that preserves resources by dynamically regulating node involvement. This model shows high scalability, low latency, enhanced security, and high energy efficiency, which we found through conducted simulations. READ-HC outperforms traditional consensus mechanisms regarding communication complexity, consensus throughput, and its adaptability to network condition variations. This makes it a viable solution for secure and efficient IIoT networks.

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Publication Details

Journal
The Journal of British Blockchain Association
Published
2025-06-02
DOI
https://doi.org/10.31585/jbba-8-2-(3)2025
Citations
1
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
3.25
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article

Reputation and Energy-Aware Dynamic Hybrid Consensus (READ-HC) Model for IIoT

Sristi Mitra, Danium Shahnowaz Syed, Vaishnavi Santosh Sable
1 citations
The Journal of British Blockchain Association
Blockchain Technology Applications and Security
3.25
article

Reputation and Energy-Aware Dynamic Hybrid Consensus (READ-HC) Model for IIoT

Sristi Mitra, Danium Shahnowaz Syed, Vaishnavi Santosh Sable
article en
1 citations

Abstract

Industry 4.0, the fourth industrial revolution, advances (Industrial IoT) IIoT with autonomous, adaptive systems capable of self-learning and self-healing. Blockchain technology offers a decentralised, safe, and auditable framework to exchange and authenticate data through transactions without relying on third parties. Private blockchains, with flexible rules and strong privacy, could therefore be deployed inside IIoT systems to address security concerns and process large volumes of data. Traditional consensus mechanisms in blockchain, such as PoW and PoS, are computationally demanding and energy-intensive and may not be suitable for resource-constrained IIoT scenarios. Centralised architectures are also vulnerable in terms of single-point failures. Therefore, this article introduces a novel blockchain-based approach, Reputation and Energy-Aware Dynamic Hybrid Consensus (READ-HC), that integrates Practical Byzantine Fault Tolerance, Proof of Reputation for emphasising reliable nodes, and an energy-efficient mechanism that preserves resources by dynamically regulating node involvement. This model shows high scalability, low latency, enhanced security, and high energy efficiency, which we found through conducted simulations. READ-HC outperforms traditional consensus mechanisms regarding communication complexity, consensus throughput, and its adaptability to network condition variations. This makes it a viable solution for secure and efficient IIoT networks.

The Journal of British Blockchain AssociationVol. 8(2)
Kadir Has University (TR)
Affordable and clean energy
Openalex Percentile: Top 7%
Blockchain Technology Applications and Security
3.25
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Reputation and Energy-Aware Dynamic Hybrid Consensus (READ-HC) Model for IIoT — Sristi Mitra, Danium Shahnowaz Syed, et al. · The Journal of British Blockchain Association (2025) | TGRS Research Map | TGRS