Suppression and Failures in Sensor Networks: A Bayesian Approach
Summary: BaySail uses Bayesian inference to disambiguate suppressed readings from message failures in energy-constrained sensor networks. Application-level redundancy beats retransmission and basic sampling on the cost–accuracy trade-off. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Adam Silberstein (Duke University)
- 2. Gavino Puggioni (Duke University)
- 3. Alan Gelfand (Duke University)
- 4. Kamesh Munagala (Duke University)
- 5. Jun Yang (Duke University)
BibTeX Citation
@article{silberstein_vldb07,
title = {{Suppression and Failures in Sensor Networks: A Bayesian Approach}},
author = {Silberstein, Adam and Puggioni, Gavino and Gelfand, Alan and Munagala, Kamesh and Yang, Jun},
journal = {PVLDB},
series = {{VLDB} '07},
year = {2007}
}
Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 12,505 | Large-Scale Uncertainty Management Systems: Learning and Exploiting Your Data (Tutorial Summary) | 2009 | SIGMOD | 5.093636e-05 |
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