A. Zyane

A novel federated learning approach for enhancing QoS and scalability in IoT networks

QoS-aware routing in software-defined internet of things: A comparative evaluation of Dijkstra and bellman–ford under heterogeneous traffic

Overall, routing efficiency depends on convergence behavior and traffic heterogeneity; Dijkstra suits latency-sensitive applications, whereas Bellman-Ford is more appropriate for adaptive routing scenarios, contributing to QoS-aware SD-IoT design.

Fuzzy-Logic-Based QoS Control in oneM2M: Adaptive Edge-to-Cloud Traffic Offloading

Maintaining a stable Quality of Service (QoS) in oneM2M deployments is challenging because edge-to-cloud traffic in IoT systems is bursty and resource demand changes rapidly. We propose a fuzzy-logic QoS controller, integrated into a MAPE-K autonomic loop, that adaptively decides the share of traffic offloaded from the...

Defending Intrusion Detection Systems from Black-Box Adversarial Threats in OneM2M-Based IoT Networks

With the proliferation of Internet of Things (IoT), critical infrastructures such as smart cities, industrial automation, precision healthcare, and intelligent transportation have seen a significant shift in their security landscape. As these critical infrastructures are increasingly depending on OneM2M standards for i...

Comparative QoS Analysis Between ITU-T Requirements and an Enhanced oneM2M Middleware: A Proof of Concept

An autonomic control architecture based on the Monitor-Analyze-Plan-Execute with Knowledge loop is integrated with a Random Forest classifier that predicts four discrete QoS operational states with 91.9% accuracy, making the compliance gap explicit and quantifiable.

IoTScal-CoM: A QoS-Aware Collaborative Middleware for Enhancing Scalability in oneM2M-based IoT Systems

The proposed IoTScal-CoM middleware employs only native oneM2M capabilities such as RTT, packet loss rate, CPU, and memory usage in order to guarantee the SLA conformity without changing the main standard specifications.

IoTScal-2CoM-ALO: An Adaptive Load Orchestration Framework for Scalable Collaborative IoT Systems

The rapid proliferation of IoT devices and ecosystems creates significant challenges in managing increasing data traffic and service requests while maintaining system performance [1]– [3]. In oneM2M-based IoT systems, overloaded Common Service Entities (CSEs) can become bottlenecks, leading to resource saturation, high...