Energy-aware blockchain consensus enhanced by graph neural networks for sustainable, scalable transaction verification across heterogeneous IoT networks
Visa Inc. USA.
Review Article
World Journal of Advanced Research and Reviews, 2023, 20(03), 2354-2373
Publication history:
Received on 20 November 2023; revised on 27 December 2023; accepted on 29 December 2023
Abstract:
The exponential growth of heterogeneous Internet of Things (IoT) networks has amplified demands for secure, scalable, and sustainable transaction verification mechanisms. Traditional blockchain consensus protocols, such as Proof-of-Work (PoW), offer robust security but impose prohibitive energy costs, limiting their viability for resource-constrained IoT environments. Proof-of-Stake (Po’s) and lightweight consensus schemes improve efficiency but often compromise scalability or fairness. To address this trade-off, this study introduces an energy-aware blockchain consensus framework enhanced by graph neural networks (GNNs) for sustainable, scalable verification across heterogeneous IoT ecosystems. In this approach, GNNs are applied to dynamically model IoT device interconnections, enabling efficient clustering, adaptive leader election, and optimized consensus pathways. By learning the structural and temporal patterns of IoT networks, GNNs reduce redundant computations and allocate verification tasks intelligently, minimizing energy consumption while maintaining security. The consensus framework integrates energy profiling of devices with predictive workload balancing, ensuring equitable participation across diverse hardware capacities. Blockchain provides the foundation for immutable, decentralized trust, while the GNN-enhanced consensus mechanism improves throughput, latency, and energy efficiency in large-scale deployments. Simulation studies of smart grids, industrial IoT, and urban sensor networks demonstrate measurable improvements in energy savings, scalability, and fault tolerance. The proposed architecture contributes to the vision of sustainable blockchain systems that can operate effectively in energy-sensitive, heterogeneous IoT contexts. By fusing blockchain’s decentralized trust with GNN-based intelligence, the framework offers a pathway toward greener, more scalable transaction verification tailored for next-generation IoT infrastructures.
Keywords:
Energy-Aware Blockchain; Graph Neural Networks; Sustainable Consensus; Iott Scalability; Transaction Verification; Heterogeneous Networks
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0