An Adaptive and Autonomous Sensor Sampling Frequency Control Scheme for Energy-Efficient Data Acquisition in Wireless Sensor Networks

Supriyo Chatterjea, Paul J.M. Havinga

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    24 Citations (Scopus)


    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.
    Original languageUndefined
    Title of host publication4th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS)
    EditorsS.E. Nikoletseas, B.S. Chlebus, D. Johnson, B. Krishnamachari
    Place of PublicationBerlin
    Number of pages19
    ISBN (Print)978-3-540-69169-3
    Publication statusPublished - 7 Jun 2008
    Event4th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2008 - Santorini, Greece
    Duration: 11 Jun 200814 Jun 2008
    Conference number: 4

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer Verlag
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference4th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2008
    Abbreviated titleDCOSS 2008
    Internet address


    • IR-62556
    • EWI-14161
    • METIS-252118

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