Optimizing Quality of Service in IoMT Through Fog Computing-Enabled Service Composition

The Internet of Medical Things (IoMT) has emerged as a paradigm shift in healthcare, allowing for remote patient monitoring and personalized treatments. However, due to the resource limitations of medical devices, the vital nature of health- care data, and the necessity for real-time response, guaranteeing Quality of Service (QoS) in IoMT systems offers considerable issues. This research presents a technique for addressing these difficulties in IoMT by exploiting Fog Computing-Enabled Service Composition. The issue statement centers on the need to improve QoS in IoMT systems, which includes response time, reliability, and energy consumption. Existing solutions struggle to match the severe criteria of IoMT, where service deployment, orchestration, and data processing must be performed in a fast, energy-efficient, and reliable way. To address these concerns, we propose a set of techniques that combine Fog Computing with service composition to optimize QoS in IoMT. The framework is proposed to incorporate dynamics service orchestration, context ware decision-making and balance the load into the IoMT systems to allow service composition at network edge. The implementation of proposed technique is done and demonstrates how computing nodes are worked inside the IoMT system to enable dynamic service composition. Our results show improvements in the QoS parameters like response times, optimized energy consumption and enhanced reliability.