ADVANCED AI TECHNIQUES IN CLOUD COMPUTING: COMPREHENSIVE ANALYSIS OF OPTIMIZATION, RESOURCE MANAGEMENT, AND SECURITY APPLICATIONS

Abstract

Cloud computing has transformed the way computational resources are provisioned, man-
aged, and optimized, driven by the increasing demand for scalable and efficient data processing capabilities.
With the exponential growth of data and the complexity of cloud infrastructures, Artificial Intelligence (AI)
has emerged as a pivotal technology in enhancing cloud operations, from optimizing resource allocation
to fortifying security measures. This paper presents a comprehensive analysis of AI applications in cloud
computing, examining various state-of-the-art AI-driven techniques across multiple dimensions, including
resource management, workload prediction, autoscaling, and security threat detection. Key methodologies
such as machine learning, deep learning, neural networks, and reinforcement learning are explored to
highlight their roles in enhancing cloud performance, reliability, and efficiency. Moreover, the review delves
into advanced optimization strategies that leverage AI for cost reduction and energy efficiency, addressing
the crucial balance between performance and sustainability in cloud environments. The paper further
discusses AI’s role in predictive analytics, enabling proactive maintenance and minimizing downtimes
in cloud systems. The integration of AI in cloud security is also emphasized, focusing on anomaly
detection, intrusion prevention, and DDoS mitigation techniques that safeguard cloud infrastructures.
Through extensive citations of recent research, this study aims to provide insights into current trends,
challenges, and future directions in AI-driven cloud computing. By synthesizing findings from various
studies, the paper underscores the transformative impact of AI on cloud computing, offering a detailed
overview that serves as a guide for researchers and practitioners aiming to leverage AI for next-generation
cloud solutions.