The design of an acquisitional query processor for sensor networks
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
TiNA: a scheme for temporal coherency-aware in-network aggregation
Proceedings of the 3rd ACM international workshop on Data engineering for wireless and mobile access
The Cougar Project: a work-in-progress report
ACM SIGMOD Record
QUASAR: quality aware sensing architecture
ACM SIGMOD Record
Stream Query Processing for Healthcare Bio-sensor Applications
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Medium access control in wireless sensor networks
Wireless sensor networks
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Confidence-driven early object elimination in quality-aware sensor workflows
DMSN '05 Proceedings of the 2nd international workshop on Data management for sensor networks
Window-aware load shedding for aggregation queries over data streams
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Semantic similarity based trust computation in websites
Workshop on multimedia information retrieval on The many faces of multimedia semantics
Top-k queries on uncertain data: on score distribution and typical answers
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Blink 'Em All: Scalable, User-Friendly and Secure Initialization of Wireless Sensor Nodes
CANS '09 Proceedings of the 8th International Conference on Cryptology and Network Security
Confidence building among correlated streams in multimedia surveillance systems
MMM'07 Proceedings of the 13th International conference on Multimedia Modeling - Volume Part II
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The military is working on embedding sensors in a "smart uniform" that will monitor key biological parameters to determine the physiological status of a soldier. The soldier's status can only be determined accurately by combining the readings from several sensors using sophisticated physiological models. Unfortunately, the physical environment and the low-bandwidth, push-based personal-area network (PAN) introduce uncertainty in the inputs to the models. Thus the model must produce a confidence level as well as a physiological status value. This paper explores how confidence levels can be used to influence data management decisions. In particular, we look at power-efficient ways to keep the confidence above a given threshold. We also contrast push-based broadcast schedules with other schedules that are made possible by two-way communication.