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What is An Efficient Federated Forcart Algorithm For Predicting and Allocating Resources in Network Function Virtualization about?

This paper presents a Federated Forcart-based framework for resource allocation in Network Function Virtualization (NFV), addressing the limitations of traditional AI methods like Deep Reinforcement Learning (DRL). The proposed framework utilizes lightweight, interpretable Machine Learning algorithms to enhance prediction accuracy, reduce latency, and maintain data privacy across distributed NFV domains. By integrating Federated Learning with a hybrid Random Forest-CART model, the framework aims to optimize

Author

ijcncjournal019

Language

EN