Enhancing Kubernetes Automated Scheduling with Deep Learning and Reinforcement Techniques for Large-Scale Cloud Computing Optimization

arXiv:2403.07905v1 Announce Type: cross
Abstract: With the continuous expansion of the scale of cloud computing applications, artificial intelligence technologies such as Deep Learning and Reinforcement Learning have gradually become the key tools to solve the automated task scheduling of large-scale cloud computing systems. Aiming at the complexity and real-time requirement of task scheduling in large-scale cloud computing system, this paper proposes an automatic task scheduling scheme based on deep learning and reinforcement learning. Firstly, the deep learning technology is used …

abstract applications artificial artificial intelligence arxiv automated become cloud cloud computing computing computing systems continuous cs.ai cs.dc cs.lg deep learning expansion intelligence key kubernetes optimization reinforcement reinforcement learning scale scheduling solve systems task scheduling technologies the key tools type