Suppression and Failures in Sensor Networks: A Bayesian Approach
Summary: BaySail, a Bayesian framework, integrates epsilon-based temporal suppression with redundancy-aware inference to mitigate missing data and ambiguity from message failures in sensor networks. It evaluates redundancy schemes, showing application-level redundancy reduces in-network transmission costs and improves out-of-network inference accuracy versus retransmission or simple sampling. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Adam Silberstein
- 2. Gavino Puggioni
- 3. Alan Gelfand
- 4. Kamesh Munagala
- 5. Jun Yang
Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 12,311 | Large-Scale Uncertainty Management Systems: Learning and Exploiting Your Data (Tutorial Summary) | 2009 | SIGMOD | 4.1945683e-05 |
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