Blockchain-enabled intelligent model for energy-constrained IoMT networks with privacy-preserving

Abstract

The Internet of Medical Things (IoMT), with the integration of physical objects, is widely explored to advance healthcare applications, enabling real-time monitoring and diagnosis of patient conditions. These systems collaborate with biosensors, allowing medical experts to track patient records and improve the efficiency of the medical system through responsive, effective systems. However, the constrained resources of the healthcare application, as well as many significant research areas in energy management, timely decision-making, and the management of massive amounts of data, still need to be addressed. Moreover, ensuring privacy in the unpredictable nature of wireless networks is another critical concern when deploying healthcare-related solutions in real-world environments. In this research, we propose a distributed intelligence-based collaborative framework for the healthcare system using an agent-driven approach, aiming to improve network energy efficiency and enable prompt responses in critical situations. In addition, trust is established through third-party interactions in a decentralized network to maintain device reputation. Thirdly, the proposed framework introduces blockchain-based security to ensure the immutability of data transmission while preserving privacy and maintaining data integrity. The proposed model is tested using the NS-3 simulator and demonstrates significant performance over the PKI-EERP, ASCP-IoMT and GWO-MARP schemes, while achieving average improvements of 52% in packet drop ratio, 45% in throughput, 34% in delay, 42% in network lifetime, 39% in energy consumption, and 30% in blockchain overhead across varying health sensors and time-variant scenarios.