This study aims to improve health-care quality by integrating diverse sources through a mobile-fog-cloud architecture and a blockchain-enabled deep reinforcement learning (DRL) model.
The framework combines mobile-fog-cloud architecture with blockchain-enabled DRL to address data security, resource allocation and workflow management. It uses deep learning and blockchain for data validation and secure transactions, supported by a symmetric cryptographic scheme for smart contracts.
Performance evaluations show significant improvements in resource utilization, reduced delays and enhanced system throughput. The proposed algorithm outperforms existing approaches in simulations.
This research introduces a novel framework that optimizes health-care workflows by combining mobile-fog-cloud architecture with blockchain-enabled DRL, providing a solid foundation for future advancements in intelligent health-care systems. The integration of DRL and blockchain into a lightweight architecture demonstrates strong potential for real-time deployment, providing a promising path toward practical, adaptive and secure IDS and workflow solutions for IoT environments.
