Application-Aware SDN Framework for Dense IoMT Networks: Dynamic TWT and OFDMA Optimisation via Hybrid AI Control

The rapid growth of Internet of Medical Things (IoMT) devices in dense hospital environments creates severe challenges for network reliability, latency, and power efficiency. Although the IEEE 802.11ax (Wi-Fi 6) standard includes features such as Target Wake Time (TWT) and Orthogonal Frequency-Division Multiple Access (OFDMA) to lower energy use and congestion, standard MAC-layer settings cannot adapt automatically to rapid shifts in traffic priority and channel quality. To resolve the fundamental operational asymmetry between ultra-low-latency critical medical telemetry and delay-tolerant bulk background traffic, this paper presents a novel Software-Defined Networking (SDN) framework combined with Fuzzy Logic control to dynamically restore resource balance in high-density IoMT networks. Developed and evaluated within the NS-3 discrete-event simulator (version 3.45), the proposed framework combines centralised SDN-Ryu orchestration with localised fuzzy logic inference. The system dynamically manages IEEE 802.11ax link-layer resources by scheduling TWT sleep/wake duty cycles at the application interface and allocating Multi-User OFDMA (MU-OFDMA) Resource Units (RUs) via a custom round-robin scheduler based on real-time traffic class, station density, and channel demand. When benchmarked against standard IEEE 802.11ax deployments and predictive approaches such as LSTM models, the hybrid SDN–Fuzzy Logic framework enhanced power consumption efficiency for critical medical IoMT devices while maintaining key Quality of Service (QoS) parameters, namely delay, jitter, and packet loss ratio, even under congested network conditions. These results demonstrate that combining centralised SDN visibility with adaptive fuzzy logic offers a reliable, scalable strategy for mission-critical IoMT applications.