Manuscript Number : IJSRST24113260

AI-Driven Resource Management in Cloud Computing : A Review

Authors(1) :-Vijay Ramamoorthi

Cloud computing has revolutionized the delivery of computational resources by providing scalable and elastic infrastructure. However, the increasing complexity of cloud environments presents significant challenges in resource management, including dynamic allocation, energy efficiency, and multi-tenant optimization. Traditional methods often fail to meet the demands of modern cloud systems, leading to inefficiencies, high operational costs, and compromised Quality of Service (QoS). This paper reviews the transformative role of Artificial Intelligence (AI) in addressing these challenges. AI-driven techniques, such as machine learning, reinforcement learning, and optimization algorithms, enable predictive analytics, adaptive scaling, and efficient workload distribution. Key applications include dynamic resource allocation, energy optimization, and intelligent scheduling in multi-tenant systems. By synthesizing current advancements and identifying challenges, this study highlights the potential of AI to enhance cloud computing efficiency, scalability, and sustainability. The findings provide a roadmap for researchers and practitioners to develop next-generation cloud systems powered by AI.

Authors and Affiliations

Vijay Ramamoorthi
Independent Researcher, USA

Cloud Computing, Artificial Intelligence, Resource Management, Multi-Tenant Optimization, Dynamic Resource Allocation, Energy Efficiency, Reinforcement Learning.

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Publication Details

Published in : Volume 11 | Issue 1 | January-February 2024
Date of Publication : 2024-02-29
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 683-696
Manuscript Number : IJSRST24113260
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Vijay Ramamoorthi, " AI-Driven Resource Management in Cloud Computing : A Review", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 11, Issue 1, pp.683-696, January-February-2024. Available at doi : https://doi.org/10.32628/IJSRST24113260    
Journal URL : https://ijsrst.com/IJSRST24113260
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