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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)

Paper ID
9634
Venue
VLDB
Year
2007
Pagerank
4.1945683e-05
Overall Rank
12,480 | 13.18%
DOI
-

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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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