Dr Narayana Rao Appini

AI-Based Dynamic Task Scheduling in Cloud Computing Using Deep Reinforcement Learning

An AI-enabled dynamic task scheduling framework based on Deep Reinforcement Learning (DRL) with a Deep Q-Network (DQN) model to dynamically assign tasks to virtual machines and learn the best scheduling policies by continuously interacting with the cloud environment based on system parameters such as resource availability, task queue length, and virtual machine load is introduced.