Vol. 2 No. 1 (2022): Journal of AI-Assisted Scientific Discovery
Articles

Towards Efficient Resource Allocation in Cloud Computing using Reinforcement Learning

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  • Dr. Aïcha Belhajjami
Dr. Aïcha Belhajjami
Associate Professor of Electrical Engineering, Cadi Ayyad University, Morocco
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Published 30-06-2022

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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. Aïcha Belhajjami, “Towards Efficient Resource Allocation in Cloud Computing using Reinforcement Learning”, Journal of AI-Assisted Scientific Discovery, vol. 2, no. 1, pp. 173–194, Jun. 2022, Accessed: Nov. 21, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/71

Abstract

Cloud computing relocates the servers at different geographical locations. It provides several advantages such as computational capability, storage, network services on demand, and proper utilization of computational resources. It provides the features to access data by using available internet. Cloud servers monitor the resources such as minimum memory and CPU utilization. Consequently, resources are wasted and business objectives are interrupted. The money is refundable to reduce unwanted resources. The reinforcement learning technique deploys the intelligent controller to increase the utility of desired resources. The controller also assigns a huge amount of pending operations in the queue of execution. The reinforcement learning technique forecasts the future behaviors. The controller instruments the proper languages as well as applications required to solve customer demands. This research article discusses the application of reinforcement learning to determine the demands of clouds from the corporate customers. The simulated results display the importance of reinforcement learning when comparing machine learning techniques.

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