A Decentralized Quality Aware Adaptive Sampling Strategy in Wireless Sensor Networks

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    104 Downloads (Pure)

    Abstract

    Since WSNs suffer from sever resource constraints, in terms of energy, memory and processing, temporal, spatial and spatio-temporal correlation among sensor data can be exploited by adaptive sampling approaches to find out an optimal sampling strategy, which reduces the number of sampling nodes and/or sampling rates while maintaining high data quality. In this paper, a quality aware decentralized adaptive sampling strategy is proposed which benefit from the data correlation for predicting future samples. In this algorithm, sensor nodes adjust their sampling rates, based on environmental conditions and user defined data range. Simulation results show that proposed approach provides 90 percentage event detection accuracy level while consumes lesser energy rather than existing adaptive sampling approach.
    Original languageUndefined
    Title of host publication9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012
    Place of PublicationUSA
    PublisherIEEE Computer Society
    Pages298-305
    Number of pages8
    ISBN (Print)978-1-4673-3084-8
    DOIs
    Publication statusPublished - Sep 2012
    EventIEEE 9th International Conference on Ubiquitous Intelligence and Computing, UIC 2012 - Fukuoka, Japan
    Duration: 4 Sep 20127 Sep 2012
    Conference number: 9

    Publication series

    Name
    PublisherIEEE Computer Society

    Conference

    ConferenceIEEE 9th International Conference on Ubiquitous Intelligence and Computing, UIC 2012
    Abbreviated titleUIC
    CountryJapan
    CityFukuoka
    Period4/09/127/09/12

    Keywords

    • EWI-22543
    • IR-83420
    • METIS-293201

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