An Intelligent Fair and Decentralized Consensus Mechanism for Blockchain-Based Supply Chain

This study focuses on fairness and latency issues in blockchain-based supply chains. To address these challenges, a novel consensus framework is developed to ensure a decentralized and efficient transaction validation process. This framework consists of three mathematical models designed to optimize global payoff, payoff allocation, and transaction processing time within a selected network of validators. A reinforcement learning technique is applied to address the inherent complexity of the transaction-scheduling problem. Simulation results demonstrate the effectiveness of the proposed model by balancing resource utilization, ensuring fair payoff distribution, and reducing processing times. These findings highlight the potential of this approach for developing decentralized and scalable blockchain-based supply chain systems.