Scalable Approximate Query Tracking over Highly Distributed Data Streams
Summary: Scalable approximate query tracking over distributed streams via Geometric Monitoring suffers when the number of sites grows. A sampling-based scheme with O(sqrt(N)) sites preserves accuracy guarantees while dramatically reducing communication, validated on real data streams. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Nikos Giatrakos (Technical University of Crete)
- 2. Antonios Deligiannakis (Technical University of Crete)
- 3. Minos Garofalakis (Technical University of Crete)
BibTeX Citation
@inproceedings{giatrakos_sigmod16,
title = {{Scalable Approximate Query Tracking over Highly Distributed Data Streams}},
author = {Giatrakos, Nikos and Deligiannakis, Antonios and Garofalakis, Minos},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2915225},
url = {https://dl.acm.org/doi/10.1145/2882903.2915225},
year = {2016}
}
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