Best-effort cache synchronization with source cooperation
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Approximate Data Collection in Sensor Networks using Probabilistic Models
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
An energy-efficient querying framework in sensor networks for detecting node similarities
Proceedings of the 9th ACM international symposium on Modeling analysis and simulation of wireless and mobile systems
ACM Transactions on Sensor Networks (TOSN)
PAQ: time series forecasting for approximate query answering in sensor networks
EWSN'06 Proceedings of the Third European conference on Wireless Sensor Networks
Evolution and sustainability of a wildlife monitoring sensor network
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
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Wireless sensor networks are increasingly being used in environmental monitoring applications. Collecting raw data from these networks can lead to excessive energy consumption. This is especially true when the application requires specialized sensors that have very high energy consumption, e.g. hydrological sensors for monitoring marine environments. We describe an adaptive sensor sampling scheme where nodes change their sampling frequencies autonomously based on the variability of the measured parameters. The sampling scheme also meets the user's sensing coverage requirements by using information provided by the underlying MAC protocol. This allows the scheme to automatically adapt to topology changes. Our results based on real and synthetic data sets, indicate a reduction in sensor sampling by up to 93%, reduction in message transmissions by up to 99% and overall energy savings of up to 87%. We also show that generally more than 90% of the collected readings fall within the user-defined error threshold.