This survey provides an overview of Edge-Fog-Cloud-IoT architectural models and the technologies that have driven them during 2020–2026 and presents a holistic framework and a five-layer reference model that encompass the functional, performance, and trust aspects of distributed systems.
The proposed framework, EcoSense-AI, combines Energy-Weighted Federated Learning, Adaptive Differential Privacy, Energy-Aware Graph Neural Network-based topology modeling, and multi-objective resource optimization to facilitate secure, efficient, and adaptive edge-cloud collaborative intelligence for sustainable WSN-Io...
The rapid proliferation of Internet of Things (IoT) devices has resulted in an unprecedented increase in the volume of data they generate. Real-time processing and analysis of IoT data are essential for enabling timely decision-making and appropriate response actions. However, conventional cloudbased architectures are...
The ongoing digital transformation in power grids has made the Internet of Things (IoT) a critical component for the development of next generation smart grids. The article provides a detailed review on technologies related to IoT and their utilization within the current power grid ecosystem that includes various IoT l...
An adaptive edge gateway for ZigBee-based IoT networks that can switch between MQTT and CoAP as needed, and shows that adaptive switching improves packet delivery by 15–20% during faults in comparison to static setups and reduces recovery time without much extra overhead.
The FMAD framework integrates multiple collaborative agents for secure communication, federated learning, and coordinated cyber defense in edge–cloud IoT environments and provides a promising foundation for intelligent agent communication and scalable autonomous cyber defense in real-world edge–cloud IoT environments.
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