Analysis of the impact of data correlation on adaptive sampling in Wireless Sensor Networks

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    Abstract

    Wireless Sensor Networks (WSNs) are often densely deployed to monitor a physical phenomenon, whose nature often exhibits temporal correlation in sequential readings. Such a dense deployment results in high correlation of sensing data in the space domain. Since WSNs suffer from sever resource constraints, temporal, spatial and spatio-temporal correlation among sensor data can be exploited to find an optimal sampling strategy, which reduces the number of sampling nodes and/or sampling rates while maintaining high data quality. In this study, we investigate the impact of the data correlation on sampling strategies, by taking both data quality and energy consumption into account.
    Original languageUndefined
    Title of host publicationNinth International Conference on Networked Sensing Systems, INSS 2012
    Place of PublicationUSA
    PublisherIEEE
    Pages1-2
    Number of pages2
    ISBN (Print)978-1-4673-1784-9
    DOIs
    Publication statusPublished - Jun 2012

    Publication series

    Name
    PublisherIEEE

    Keywords

    • EWI-22541
    • METIS-293200
    • IR-83419

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