| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 133 |
| Year of Publication: 2026 |
| Authors: Anouar Ben Halima, Hafssa Benaboud |
10.5120/ijca8bbe6929f23b
|
Anouar Ben Halima, Hafssa Benaboud . Evaluation and Combining of Load-balancing AI-driven Models, including IaCloud Model. International Journal of Computer Applications. 187, 133 ( Aug 2026), 1-7. DOI=10.5120/ijca8bbe6929f23b
Large Language Models (LLMs) have recently achieved significant progress in natural language processing tasks, including question answering and assisting users, such as in cloud computing. Cloud computing is a composite of various fields, including LLMs, which is a straightforward approach to enhancing the performance of the entire cloud. Therefore, AI-driven load balancing has been developed in cloud computing for a long period to benefit from machine learning to enhance the performance of cloud computing. This study presents a comparative evaluation of several state-of-the-art LLMs, including OpenAI GPT-4 and Google Gemini, with our proposed model (IaCloud1) in predicting the most appropriate load-balancing techniques in the cloud environment.