Abstract
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.
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Chatterjea, S., Havinga, P. (2008). An Adaptive and Autonomous Sensor Sampling Frequency Control Scheme for Energy-Efficient Data Acquisition in Wireless Sensor Networks. In: Nikoletseas, S.E., Chlebus, B.S., Johnson, D.B., Krishnamachari, B. (eds) Distributed Computing in Sensor Systems. DCOSS 2008. Lecture Notes in Computer Science, vol 5067. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69170-9_5
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DOI: https://doi.org/10.1007/978-3-540-69170-9_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69169-3
Online ISBN: 978-3-540-69170-9
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