most citedVELO: A Vector Database-Assisted Cloud-Edge Collaborative LLM QoS Optimization Framework

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.DC2024

Low-Latency Layer-Aware Proactive and Passive Container Migration in Meta Computing

Mengjie Liu, Yihua Li, Fangyi Mou +4

Meta computing is a new computing paradigm that aims to efficiently utilize all network computing resources to provide fault-tolerant, personalized services with strong security an…

cs.AI20241 cited

VELO: A Vector Database-Assisted Cloud-Edge Collaborative LLM QoS Optimization Framework

Zhi Yao, Zhiqing Tang, Jiong Lou +2

The Large Language Model (LLM) has gained significant popularity and is extensively utilized across various domains. Most LLM deployments occur within cloud data centers, where the…

cs.DC2023

Efficient Serverless Function Scheduling at the Network Edge

Jiong Lou, Zhiqing Tang, Shijing Yuan +3

Serverless computing is a promising approach for edge computing since its inherent features, e.g., lightweight virtualization, rapid scalability, and economic efficiency. However,…

cs.DC2023

Joint Task Scheduling and Container Image Caching in Edge Computing

Fangyi Mou, Zhiqing Tang, Jiong Lou +3

In Edge Computing (EC), containers have been increasingly used to deploy applications to provide mobile users services. Each container must run based on a container image file that…

cs.DC2023

Online Container Scheduling for Low-Latency IoT Services in Edge Cluster Upgrade: A Reinforcement Learning Approach

Hanshuai Cui, Zhiqing Tang, Jiong Lou +1

In Mobile Edge Computing (MEC), Internet of Things (IoT) devices offload computationally-intensive tasks to edge nodes, where they are executed within containers, reducing the reli…