IoT Enabled Sustainable Health Monitoring System using Scheduling Approach and Priority Validation for Smart Healthcare Enhancement

Abstract

In this article, we propose a health tracking system designed to aid patients and doctors within a hospital campus. We primarily focus on efficiency, trust ability and scalability of the healthcare system. In previous studies, scheduling methods such as shortest task first and first-come, first-served have been commonly assumed for IoT-dependent healthcare systems. However, these approaches have limitations when it comes to accommodating a wide range of requests and efficiently handling high-demand situations. Specifically, the inclusion of short procedures in such scheduling methods can result in prolonged task completion durations and poor performance in overloaded scenarios. To deal with such challenges we proposed an analytical framework of scheduling that offers service differentiation concerning delay-sensitive, tolerant packets and packet length for a short packet being transferred before long packets. The performance of the prioritized method has been compared with the existing scheduling approaches in terms of packet loss, latency tolerance, packet threshold, mean turndown etc. to analyze its sustainability. Also, the proposed model is analyzed using two existing protocols with different simulation parameters to aiming to identify the most suitable protocol for better management of the health monitoring system.