Towards cloud-edge collaborative online video analytics with fine-grained serverless pipelines

Author:

Zhang Miao1,Wang Fangxin2,Zhu Yifei3,Liu Jiangchuan1,Wang Zhi4

Affiliation:

1. Simon Fraser University

2. The Chinese University of Hong Kong, Shenzhen

3. University of Michigan and Shanghai Jiao Tong University

4. Tsinghua University

Funder

Shenzhen Science and Technology Program

SJTU Explore-X Research

Key Area R&D Program of Guangdong Province

Publisher

ACM

Reference56 articles.

Cited by 24 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. AI-Driven QoS-Aware Scheduling for Serverless Video Analytics at the Edge;Information;2024-08-13

2. Tangram: High-Resolution Video Analytics on Serverless Platform with SLO-Aware Batching;2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS);2024-07-23

3. Color-based Lightweight Utility-aware Load Shedding for Real-Time Video Analytics at the Edge;Proceedings of the 18th ACM International Conference on Distributed and Event-based Systems;2024-06-24

4. Data pipeline approaches in serverless computing: a taxonomy, review, and research trends;Journal of Big Data;2024-06-11

5. SplitStream: Distributed and workload-adaptive video analytics at the edge;Journal of Network and Computer Applications;2024-05

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