LTC: a Fast Algorithm to Accurately Find Significant Items in Data Streams

Author:

Cheng Shiyu,Yang Dongsheng,Yang Tong,Zhang Haowei,Cui Bin

Funder

FANet: PCL Future Greater-Bay Area Network Facilities for Large-scale Experiments and Applications

National Natural Science Foundation of China

Primary Research and Development Plan of China

PKU-Baidu Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Cited by 5 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. Conditional heavy hitter monitoring and application of heterogeneous graph streams based on sketches;Information Processing & Management;2024-07

2. BurstDetector: Real-Time and Accurate Across-Period Burst Detection in High-Speed Networks;IEEE INFOCOM 2024 - IEEE Conference on Computer Communications;2024-05-20

3. CBA Sketch: A Sketching Algorithm Mining Persistent Batches in Data Streams;Lecture Notes in Computer Science;2024

4. Sketch-based Real-time Intrusion Detection Framework for Industrial Internet of Things;2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS);2023-12-17

5. Tight-Sketch: A High-Performance Sketch for Heavy Item-Oriented Data Stream Mining with Limited Memory Size;Proceedings of the 32nd ACM International Conference on Information and Knowledge Management;2023-10-21

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