AI-Enhanced Cloud Computing: Comprehensive Review of Resource Management, Fault Tolerance, and Security

Abstract

Cloud computing is pivotal in today’s digital landscape, providing scalable, flexible, and cost-effective solutions for data storage, processing, and application deployment. However, as cloud environments become more complex, challenges such as resource management, fault tolerance, and security intensify. Artificial Intelligence (AI) has emerged as a transformative technology that addresses these challenges, offering innovative solutions for predictive analytics, dynamic resource allocation, proactive fault management, and enhanced security protocols. This paper reviews the extensive application of AI in cloud computing, including AI-driven load prediction, task scheduling, deep learning models for predictive maintenance, and AI-based intrusion detection systems. Key techniques discussed involve machine learning, deep learning, and heuristic algorithms that optimize cloud performance, reduce costs, and ensure high reliability. Despite these advancements, several challenges remain, including data quality, integration complexity, and the vulnerability of AI models to adversarial attacks. This review provides a detailed synthesis of AI’s role in cloud computing, highlighting successes, limitations, and future research directions to guide the evolution of more intelligent, efficient, and secure cloud environments.