activity
20212026
most citedAnalytically-Driven Resource Management for Cloud-Native Microservices

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.DC2026

Trident: Adaptive Scheduling for Heterogeneous Multimodal Data Pipelines

Ding Pan, Zhuangzhuang Zhou, Long Qian +1

The rapid adoption of large language models and multimodal foundation models has made multimodal data preparation pipelines critical AI infrastructure. These pipelines interleave C…

cs.DC2024★ 1 cited

Analytically-Driven Resource Management for Cloud-Native Microservices

Yanqi Zhang, Zhuangzhuang Zhou, Sameh Elnikety +1

Resource management for cloud-native microservices has attracted a lot of recent attention. Previous work has shown that machine learning (ML)-driven approaches outperform traditio…

cs.DC2022★ 1 cited

QoS-Aware Resource Management for Multi-phase Serverless Workflows with Aquatope

Zhuangzhuang Zhou, Yanqi Zhang, Christina Delimitrou

Multi-stage serverless applications, i.e., workflows with many computation and I/O stages, are becoming increasingly representative of FaaS platforms. Despite their advantages in t…

cs.DC2021

Sinan: Data Driven Resource Management for Cloud Microservices

Yanqi Zhang, Weizhe Hua, Zhuangzhuang Zhou +2

Cloud applications are increasingly shifting to interactive and loosely-coupled microservices. Despite their advantages, microservices complicate resource management, due to inter-…

cs.DC2021

Sinan: Data-Driven, QoS-Aware Cluster Management for Microservices

Yanqi Zhang, Weizhe Hua, Zhuangzhuang Zhou +2

Cloud applications are increasingly shifting from large monolithic services, to large numbers of loosely-coupled, specialized microservices. Despite their advantages in terms of fa…