6 papers
HeraSys: Collaborative Serving of Multiple LLM Workflows via Fine-Grained End-to-End Optimization
Size Li, Zhiqing Tang, Hongrui Liang +4
The proliferation of Large Language Models (LLMs) has shifted serving systems from processing isolated requests to orchestrating high-concurrency, multi-tenant agentic workflows. H…
BWCache: Accelerating Video Diffusion Transformers through Block-Wise Caching
Hanshuai Cui, Zhiqing Tang, Zhifei Xu +3
Recent advancements in Diffusion Transformers (DiTs) have established them as the state-of-the-art method for video generation. However, their inherently sequential denoising proce…
Adaptive AI Agent Placement and Migration in Edge Intelligence Systems
Xingdan Wang, Jiayi He, Zhiqing Tang +5
The rise of LLMs such as ChatGPT and Claude fuels the need for AI agents capable of real-time task handling. However, migrating data-intensive, multi-modal edge workloads to cloud…
EAT: QoS-Aware Edge-Collaborative AIGC Task Scheduling via Attention-Guided Diffusion Reinforcement Learning
Zhifei Xu, Zhiqing Tang, Jiong Lou +5
The growth of Artificial Intelligence (AI) and large language models has enabled the use of Generative AI (GenAI) in cloud data centers for diverse AI-Generated Content (AIGC) task…
LRScheduler: A Layer-aware and Resource-adaptive Container Scheduler in Edge Computing
Zhiqing Tang, Wentao Peng, Jianxiong Guo +5
Lightweight containers provide an efficient approach for deploying computation-intensive applications in network edge. The layered storage structure of container images can further…
Hybrid Learning for Cold-Start-Aware Microservice Scheduling in Dynamic Edge Environments
Jingxi Lu, Wenhao Li, Jianxiong Guo +4
With the rapid growth of IoT devices and their diverse workloads, container-based microservices deployed at edge nodes have become a lightweight and scalable solution. However, exi…