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Model-Driven Data Acquisition in Sensor Networks

Summary: Enriches declarative sensor queries with statistical models to map readings to reality and provide probabilistic confidence. Presents an optimization to select readings under cost, with an exponential-time exact solver and a practical polynomial-time heuristic, achieving high fidelity and gains over traditional acquisition. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9167
Venue
VLDB
Year
2004
Pagerank
0.00022221803
Overall Rank
477 | 96.69%
DOI
-

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