ICN caching for efficient patient centric healthcare data access in internet of medical things systems

Abstract Internet of Medical Things (IoMT) is built with various medical equipment to improve healthcare technology, including smart devices, hardware infrastructure, and software applications. The network experiences massive data traffic due to the data generated by these medical devices. Controlling this data flow while meeting user expectations becomes difficult. Information Centric Network (ICN) networks are employed to overcome data management problems and effectively handle data transfer in a network. This work aims to develop a patient-centric approach for IoMT to optimize healthcare data access using ICN in-network caching by prioritizing the content and categorizing the content based on the patient’s disease ranking. A two-queue technique with dynamic caching is presented in this paper for effective caching at edge devices. Every content item is divided into four categories, and each edge router maintains two queues to store the content based on priority. Age and disease ranking fields are added to interest and data packets to identify the type of content. Based on the frequency of access, the content in the edge routers is dynamically updated. Least Recently Used (LRU) based prioritized queue cache replacement algorithm is proposed to replace content in each queue by prioritizing emergency content. The proposed work is evaluated in terms of cache hit ratio, content latency, and the stretch ratio in a Java-based Java Information Centric Cache Network Simulator (JICCNS) simulator. The performance of the proposed work shows better results than existing strategies and ensures optimal cache utilization and data retrieval efficiency.