AI-Augmented Software-Defined Networking (SDN) in Cloud Environments
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V4I4P101Keywords:
AI-Augmented SDN, Software-Defined Networking, Machine Learning, Deep Learning, Reinforcement Learning, Network Optimization, Traffic Prediction, Anomaly Detection, Cloud Computing, Network SecurityAbstract
Software-Defined Networking (SDN) has emerged as a revolutionary paradigm in network management, offering centralized control and programmability. The integration of Artificial Intelligence (AI) with SDN, referred to as AI-Augmented SDN, further enhances the capabilities of SDN by enabling intelligent decision-making, predictive analytics, and autonomous network operations. This paper explores the current state and future potential of AIAugmented SDN in cloud environments. We discuss the architectural frameworks, key technologies, and practical applications of AI-Augmented SDN. Additionally, we analyze the benefits, challenges, and future research directions in this domain. The paper concludes with a discussion on the implications of AI-Augmented SDN for cloud service providers and end-users
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