An Investigation into the Optimization of Resource Allocation in Cloud Computing Environments Utilizing Artificial Intelligence Techniques

Abstract

Cloud computing has revolutionized the way businesses and organizations manage their IT infrastructure by providing on-demand access to computing resources. However, the efficient allocation of these resources remains a significant challenge due to the dynamic and unpredictable nature of user demands. This research article explores the application of artificial intelligence (AI) techniques to optimize resource allocation in cloud computing environments. By leveraging machine learning algorithms and deep learning models, we aim to develop intelligent systems that can accurately predict resource requirements and dynamically allocate resources to maximize utilization and minimize costs. The article presents a comprehensive analysis of existing AI-based resource allocation approaches, discusses their strengths and limitations, and proposes a novel framework that combines multiple AI techniques to achieve optimal resource allocation in various cloud computing scenarios. The proposed framework is evaluated through extensive simulations and real-world case studies, demonstrating its effectiveness in improving resource utilization, reducing costs, and enhancing the overall performance of cloud computing systems. The findings of this research have significant implications for cloud service providers, enabling them to offer more efficient and cost-effective services to their customers while ensuring high levels of performance and reliability.