Resource Efficiency-Driven Consensus (REDC): A Machine Learning-Based Blockchain Framework for Healthcare IoT Systems

The increasing adoption of Internet of Things (IoT) devices in smart healthcare systems has revolutionized real-time data collection and processing, substantially improving healthcare delivery and operational efficiency. However, the sensitivity of medical data and the resource limitations of IoT devices demand blockchain solutions that are secure, lightweight, and scalable. This paper presents two core contributions: (1) Resource Efficiency-Driven Consensus (REDC), a machine learning–enhanced consensus protocol tailored for healthcare IoT networks, and (2) Dynamic Lightweight Hashing (DLH), a cryptographic algorithm designed for energy-constrained environments. REDC achieves up to 70% higher throughput, 43% Energy Efficiency (EE), and 25% lower latency compared to Proof of Elapsed Work and Luck (PoEWAL) in networks up to 100 nodes. DLH further enhances performance by reducing hash attempts and energy use while maintaining strong collision resistance across 100,000 trials. Together, REDC and DLH form a scalable and secure blockchain framework tailored for healthcare IoT.

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Publication Details

Journal
International Journal of Mathematical Engineering and Management Sciences
Published
2025-10-12
DOI
https://doi.org/10.33889/ijmems.2025.10.6.096
Primary Topic
Blockchain Technology Applications and Security
Type
article
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article

Resource Efficiency-Driven Consensus (REDC): A Machine Learning-Based Blockchain Framework for Healthcare IoT Systems

Saurabh Jain, Adarsh Kumar
International Journal of Mathematical Engineering and Management Sciences
Blockchain Technology Applications and Security
article

Resource Efficiency-Driven Consensus (REDC): A Machine Learning-Based Blockchain Framework for Healthcare IoT Systems

Saurabh Jain, Adarsh Kumar
article en

Abstract

The increasing adoption of Internet of Things (IoT) devices in smart healthcare systems has revolutionized real-time data collection and processing, substantially improving healthcare delivery and operational efficiency. However, the sensitivity of medical data and the resource limitations of IoT devices demand blockchain solutions that are secure, lightweight, and scalable. This paper presents two core contributions: (1) Resource Efficiency-Driven Consensus (REDC), a machine learning–enhanced consensus protocol tailored for healthcare IoT networks, and (2) Dynamic Lightweight Hashing (DLH), a cryptographic algorithm designed for energy-constrained environments. REDC achieves up to 70% higher throughput, 43% Energy Efficiency (EE), and 25% lower latency compared to Proof of Elapsed Work and Luck (PoEWAL) in networks up to 100 nodes. DLH further enhances performance by reducing hash attempts and energy use while maintaining strong collision resistance across 100,000 trials. Together, REDC and DLH form a scalable and secure blockchain framework tailored for healthcare IoT.

International Journal of Mathematical Engineering and Management SciencesVol. 10(6)
University of Petroleum and Energy Studies (IN), Universitat Politècnica de Catalunya (ES)
Openalex Percentile: Top 58%
Blockchain Technology Applications and Security
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Resource Efficiency-Driven Consensus (REDC): A Machine Learning-Based Blockchain Framework for Healthcare IoT Systems — Saurabh Jain, Adarsh Kumar · International Journal of Mathematical Engineering and Management Sciences (2025) | TGRS Research Map | TGRS