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Pontus: Finding Waves in Data Streams

Summary: Defines waves as deviations in arrival rate; Pontus uses a data-plane preprocessor and a lean control-plane detector. Proposes Multi-Stage Progressive Tracking with Stage Variance Maximization; provable error bounds; P4 implementation yields 842× throughput. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h111f70370a9bb7b6
Venue
SIGMOD
Year
2023
Pagerank
5.2283159e-05
Overall Rank
9,080 | 38.96%
DOI
10.1145/3588960

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zhang_sigmod23,
        title = {{Pontus: Finding Waves in Data Streams}},
        author = {Zhang, Zhengxin and Li, Qing and Duan, Guanglin and Zhao, Dan and Xiao, Jingyu and Xie, Guorui and Jiang, Yong},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3588960},
        url = {https://dl.acm.org/doi/10.1145/3588960},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
10,534 SieveSketch: A Fine-grained and Adaptive Sketch Framework for Accurate Frequency Estimation 2026 SIGMOD 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
3,678 Quantiles over Data Streams: An Experimental Study 2013 SIGMOD 7.104636e-05
3,980 BurstSketch: Finding Bursts in Data Streams 2021 SIGMOD 6.8788724e-05
6,816 Out of Many We are One: Measuring Item Batch with Clock-Sketch 2021 SIGMOD 5.6731874e-05
7,180 On-Off Sketch: A Fast and Accurate Sketch on Persistence 2021 VLDB 5.5928753e-05
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