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Monitoring Distributed Streams using Convex Decompositions

Summary: Introduces a convex-decomposition framework for distributed monitoring of nonlinear stream queries, formally guaranteed to match or outperform covering-sphere decompositions. Applies it to sketch-based norm, range-aggregate, and join-aggregate tracking, with substantial gains on real streams. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11354
Venue
VLDB
Year
2015
Pagerank
5.093636e-05
Overall Rank
12,155 | 16.61%
DOI
10.14778/2735479.2735486

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@article{lazerson_vldb15,
        title = {{Monitoring Distributed Streams using Convex Decompositions}},
        author = {Lazerson, Arnon and Sharfman, Izchak and Keren, Daniel and Schuster, Assaf and Garofalakis, Minos and Samoladas, Vasilis},
        journal = {PVLDB},
        series = {{VLDB} '15},
        volume = {8},
        number = {5},
        pages = {545--556},
        doi = {10.14778/2735479.2735486},
        url = {https://doi.org/10.14778/2735479.2735486},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
11,536 AutoMon: Automatic Distributed Monitoring for Arbitrary Multivariate Functions 2022 SIGMOD 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 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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