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Estimating Cardinality for Arbitrarily Large Data Stream With Improved Memory Efficiency

  • Published:2020-04 Issue:2 Volume:28 Page:433-446
  • ISSN:1063-6692
  • Container-title:IEEE/ACM Transactions on Networking
  • language:
  • Short-container-title:IEEE/ACM Trans. Networking

Author:

Xiao QingjunORCID,Chen ShigangORCID,Zhou You,Luo Junzhou

Funder

National Natural Science Foundation of China

Jiangsu Provincial Key Laboratory of Computer Networking Technology

National Science Foundation of the United States

Florida Cybersecurity Center

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Computer Science Applications,Software

Cited by 23 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. A Compact and Accurate Sketch for Estimating a Large Range of Set Difference Cardinalities;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

2. An LDP Compatible Sketch for Securely Approximating Set Intersection Cardinalities;Proceedings of the ACM on Management of Data;2024-03-12

3. UltraLogLog: A Practical and More Space-Efficient Alternative to HyperLogLog for Approximate Distinct Counting;Proceedings of the VLDB Endowment;2024-03

4. Accurate and O(1)-Time Query of Per-Flow Cardinality in High-Speed Networks;IEEE/ACM Transactions on Networking;2023-12

5. Towards Accurate and Efficient Super Spreader Detection with Sketching;2023 8th International Conference on Data Science in Cyberspace (DSC);2023-08-18
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