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Efficient and Error-bounded Spatiotemporal Quantile Monitoring in Edge Computing Environments

Summary: Edge SQM framework virtualizes edge sketches; a coordinator synchronizes processing and tunes data fractions to bound error and latency. Grid-based subquerying with shared sketches and a relaxation approach yields bounded latency and error guarantees; tested on fast IoT streaming data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12865
Venue
VLDB
Year
2022
Pagerank
5.093636e-05
Overall Rank
11,569 | 20.63%
DOI
10.14778/3538598.3538600

Incoming Non-self Citations Over Time

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Authors

BibTeX Citation

@article{li_vldb22,
        title = {{Efficient and Error-bounded Spatiotemporal Quantile Monitoring in Edge Computing Environments}},
        author = {Li, Huan and Yi, Lanjing and Tang, Bo and Lu, Hua and Jensen, Christian S.},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {9},
        pages = {1753--1765},
        doi = {10.14778/3538598.3538600},
        url = {https://doi.org/10.14778/3538598.3538600},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

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Rank Citing Paper Year Venue Pagerank
10,739 TEQ: An Open and Developer-friendly Testbed for Edge-based Query Processing Algorithms 2025 SIGMOD 5.093636e-05
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