Optimization of cloud computing resource management using reinforcement learning
Table Of Contents
<p>1. Introduction<br> 1.1 Background<br> 1.2 Objectives<br> 1.3 Significance of resource optimization<br>2. Literature Review<br> 2.1 Cloud resource management challenges<br> 2.2 Reinforcement learning in resource allocation<br>3. System Architecture<br> 3.1 Cloud infrastructure components<br> 3.2 Reinforcement learning framework<br>4. Implementation<br> 4.1 Data collection and preprocessing<br> 4.2 Reinforcement learning model integration<br>5. Performance Evaluation<br> 5.1 Workload scenarios<br> 5.2 Performance metrics<br></p>
Project Abstract
This project aims to optimize cloud computing resource management using reinforcement learning techniques to dynamically allocate and scale resources based on workload demands and performance objectives. By leveraging reinforcement learning algorithms, the project seeks to enhance the efficiency, cost-effectiveness, and scalability of cloud infrastructure while ensuring high-quality service delivery to cloud users.
Project Overview
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