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Randomized Algorithms for Tracking Distributed Count, Frequencies, and Ranks

Summary: Randomized protocols reduce communication for continuous distributed count-tracking from Θ(k/ε · log N) to Θ(√k/ε · log N) with O(1) space per player and a matching lower bound. Technique extends to frequency- and rank-tracking giving analogous √k improvements over deterministic algorithms. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1586
Venue
PODS
Year
2012
Pagerank
6.3677694e-05
Overall Rank
4,190 | 70.89%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank Citing Paper Year Venue Pagerank
4,716 Weighted Reservoir Sampling from Distributed Streams 2019 PODS 5.9692227e-05
6,603 Continuous Matrix Approximation on Distributed Data 2014 VLDB 4.9923197e-05
6,717 Continuous Distributed Counting for Non-monotonic Streams 2012 PODS 4.9459755e-05
7,452 Distributed Online Tracking 2015 SIGMOD 4.7218383e-05
11,436 Model Counting meets F0 Estimation 2021 PODS 4.1905499e-05
11,831 Variability in Data Streams 2016 PODS 4.1905499e-05
11,861 Scalable Approximate Query Tracking over Highly Distributed Data Streams 2016 SIGMOD 4.1905499e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 cited papers.

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

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