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Continuous Distributed Counting for Non-monotonic Streams

Summary: Randomized algorithms for continual distributed counting on non‑monotonic streams with unknown drift μ, adversarial site assignment but random arrivals, achieving expected communication Õ(min{k/(|μ|ε), k n/ε, n}) with matching lower bounds. Extends to fractional Brownian inputs and yields F2 estimation and Bayesian linear regression applications. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1586
Venue
PODS
Year
2012
Pagerank
5.7496345e-05
Overall Rank
6,871 | 52.86%
DOI
10.1145/2213556.2213597

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{liu_pods12,
        address = {New York, NY, USA},
        series = {{PODS} '12},
        title = {{Continuous Distributed Counting for Non-monotonic Streams}},
        url = {https://dl.acm.org/doi/10.1145/2213556.2213597},
        doi = {10.1145/2213556.2213597},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Liu, Zhenming and Radunović, Božidar and Vojnović, Milan},
        year = {2012}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
12,026 Variability in Data Streams 2016 PODS 5.093636e-05
12,054 Scalable Approximate Query Tracking over Highly Distributed Data Streams 2016 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

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

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