Enabling epsilon-Approximate Querying in Sensor Networks
Summary: Introduces epsilon-approximate querying (EAQ), an incremental refinement model that avoids a priori error bounds and communicates only the precision needed. A data-shuffling algorithm encodes readings as multi-version arrays, enabling guaranteed-error approximations for diverse sensor-network queries. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Yu Liu (Harbin Engineering University)
- 2. Jianzhong Li (Harbin Engineering University)
- 3. Hong Gao (Harbin Engineering University)
- 4. Xiaolin Fang (Harbin Engineering University)
BibTeX Citation
@article{liu_vldb09,
title = {{Enabling epsilon-Approximate Querying in Sensor Networks}},
author = {Liu, Yu and Li, Jianzhong and Gao, Hong and Fang, Xiaolin},
journal = {PVLDB},
series = {{VLDB} '09},
doi = {10.14778/1687627.1687647},
url = {https://doi.org/10.14778/1687627.1687647},
year = {2009}
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9 | Online Aggregation | 1997 | SIGMOD | 0.00077458002 |
| 307 | Approximate Query Processing Using Wavelets | 2000 | VLDB | 0.00021792475 |
| 337 | Model-Driven Data Acquisition in Sensor Networks | 2004 | VLDB | 0.00020783399 |
| 2,340 | Online Outlier Detection in Sensor Data Using Non-Parametric Models | 2006 | VLDB | 8.7246796e-05 |
| 3,034 | Compressing Historical Information in Sensor Networks | 2004 | SIGMOD | 7.8302786e-05 |
| 7,414 | GAMPS: Compressing Multi Sensor Data by Grouping and Amplitude Scaling | 2009 | SIGMOD | 5.624223e-05 |
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