Advances in AI and ML for Cloud Computing: A Review of Algorithms, Challenges, and Innovations
DOI:
https://doi.org/10.32628/IJSRST2513120Keywords:
Cloud computing, Artificial Intelligence, Machine Learning, Dynamic resource allocation, Predictive analytics, Sustainability, Federated learning, Explainable AIAbstract
This review delves into the role of Artificial Intelligence (AI) and Machine Learning (ML) in revolutionizing cloud computing. It explores how AI/ML algorithms optimize resource management, enhance system scalability, strengthen security, and reduce operational costs. The paper categorizes AI/ML applications into domains such as dynamic resource allocation, anomaly detection, predictive analytics, and cost optimization. Key challenges, including scalability, data privacy, and interoperability, are discussed alongside emerging opportunities like federated learning for privacy-aware applications, explainable AI for transparent cloud management, and energy-efficient algorithms for sustainable cloud computing. This review underscores AI/ML's transformative potential while emphasizing the need for innovative solutions to overcome implementation challenges.
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