4 papers
Autonomous Resource Management in Microservice Systems via Reinforcement Learning
Yujun Zou, Nia Qi, Yingnan Deng +3
This paper proposes a reinforcement learning-based method for microservice resource scheduling and optimization, aiming to address issues such as uneven resource allocation, high l…
Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach
Shuangquan Lyu, Yingnan Deng, Guiran Liu +2
This paper addresses the limited transfer and adaptation capabilities of large language models in low-resource language scenarios. It proposes a unified framework that combines a k…
Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning
Yang Wang, Tengda Tang, Zhou Fang +2
To address the challenges of high resource dynamism and intensive task concurrency in microservice systems, this paper proposes an adaptive resource scheduling method based on the…
Dynamic Operating System Scheduling Using Double DQN: A Reinforcement Learning Approach to Task Optimization
Xiaoxuan Sun, Yifei Duan, Yingnan Deng +3
In this paper, an operating system scheduling algorithm based on Double DQN (Double Deep Q network) is proposed, and its performance under different task types and system loads is…