4 papers
AgentLoop: Runtime Control of Slot-closed Execution Loops for Tool-augmented LLM Agents
Wanyi Zheng, Minxian Xu, Kan Hu +2
Tool-augmented large language model (LLM) agents are becoming an important execution unit in service computing, but existing agent loops still lack explicit runtime signals for ass…
TD3-Sched: Learning to Orchestrate Container-based Cloud-Edge Resources via Distributed Reinforcement Learning
Shengye Song, Minxian Xu, Kan Hu +2
Resource scheduling in cloud-edge systems is challenging as edge nodes run latency-sensitive workloads under tight resource constraints, while existing centralized schedulers can s…
LSRAM: A Lightweight Autoscaling and SLO Resource Allocation Framework for Microservices Based on Gradient Descent
Kan Hu, Minxian Xu, Kejiang Ye +1
Microservices architecture has become the dominant architecture in cloud computing paradigm with its advantages of facilitating development, deployment, modularity and scalability.…
MSARS: A Meta-Learning and Reinforcement Learning Framework for SLO Resource Allocation and Adaptive Scaling for Microservices
Kan Hu, Linfeng Wen, Minxian Xu +1
Service Level Objectives (SLOs) aim to set threshold for service time in cloud services to ensure acceptable quality of service (QoS) and user satisfaction. Currently, many studies…