TAG: a Tiny AGgregation service for ad-hoc sensor networks
ACM SIGOPS Operating Systems Review - OSDI '02: Proceedings of the 5th symposium on Operating systems design and implementation
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
ACE in the Hole: Adaptive Contour Estimation Using Collaborating Mobile Sensors
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Asynchronous in-network prediction: Efficient aggregation in sensor networks
ACM Transactions on Sensor Networks (TOSN)
Tracking dynamic boundary fronts using range sensors
EWSN'08 Proceedings of the 5th European conference on Wireless sensor networks
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Much of the data consumed today is dynamic, typically gathered from distributed sources including sensors, and used in real-time monitoring and decision making applications. Large scale sensor networks are being deployed for applications such as detecting leakage of hazardous material, tracking forest fires or environmental monitoring. Many of these "natural" phenomena require estimation of their future states, based on the observed dynamics. Strategically deployed sensors can operate unattended (minimizing risk to human life) and provide the ability to continuously monitor the phenomena and help respond to the changes in a timely manner. In this paper, we show that in-network aggregation, in-network prediction, and asynchronous information dissemination form sound building blocks for addressing the challenges in developing low overhead solutions to monitor changes without requiring prior knowledge about the (dynamics of) the phenomena being monitored.