Optimizing Resource Allocation in Cloud Computing Using AI-Driven Techniques

Devika, M and Sowmiya Sree, C and Yamini, B. and Shobana, P. and Jegathambal, P. M. G. and Subalakshmi, C and Christina Angelin, C and Prasanna Ranjith, Christodoss (2026) Optimizing Resource Allocation in Cloud Computing Using AI-Driven Techniques. In: AI-Driven Sustainable and Secure Smart Infrastructure Systems. IGI Global Scientific Publishing, pp. 343-368. ISBN 9798337321424

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Abstract

Through the provision of elastic, on-demand resources to business users and consumers, cloud computing has revolutionised the information technology industry. It is not possible to achieve appropriate resource assignment due to the fact that the user's requirements and responsibilities are always going through changes. In this article, artificial intelligence-based techniques such as reinforcement learning and machine learning are analysed with the goal of successfully assigning resources in cloud frameworks in the most efficient manner possible. Through the utilisation of real-time decision-making in conjunction with predictive analytics, these strategies enable their processes to become more productive, less expensive, and more dependable in terms of service. In addition to this, the study investigates the possibilities for optimising cloud resources through the use of containerisation and peripheral computing.

Item Type: Book Section
Subjects: Computer Science Engineering > Cloud Computing
Domains: Computer Science Engineering
Depositing User: Mr IR Admin
Last Modified: 11 May 2026 05:39
URI: https://ir.vistas.ac.in/id/eprint/15789

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