Algorithms for energy efficient data extraction from wireless sensor networks for environmental monitoring applications

Supriyo Chatterjea, Paul J.M. Havinga

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

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    Abstract

    Wireless sensor networks (WSNs) can provide high resolution spatial and temporal data for environmental applications if they are densely deployed. However, as the nodes which make up the network are typically battery operated, a major problem faced by WSNs is limited network lifetime. In order to extend network lifetime to several years, the radio transceiver and attached sensors need to be managed carefully to minimize power consumption. This paper provides an overview of two separate solutions that we are currently testing in a real-life application on the Great Barrier Reef (GBR). The first algorithm minimizes transmissions by taking advantage of spatial correlations of sensor readings while the second algorithm minimizes sensor sampling operations by taking advantage of the temporal correlations that exist between successive sensor readings. Both the solutions have been developed as part of our efforts together with the Australian Institute of Marine Science, to deploy a large scale WSN on the Great Barrier Reef (GBR). This network will be used to study the effects of global warming and agriculture on the coral reefs. Details of our deployment of sensor nodes on the GBR using buoys are also described.
    Original languageUndefined
    Title of host publicationProceedings of International Workshop Sensing a Changing World 2008
    EditorsL Kooistra, A Ligtenberg
    Place of PublicationWageningen
    PublisherWageningen University and Research Centre
    Pages15-18
    Number of pages4
    ISBN (Print)1568-1874
    Publication statusPublished - Nov 2008

    Publication series

    NameCGI report
    PublisherWageningen University and Research Centre
    NumberCGI-08-005
    ISSN (Print)1568-1874

    Keywords

    • environmental monitoring
    • EWI-15126
    • IR-65402
    • METIS-255894
    • Sensor Networks

    Cite this

    Chatterjea, S., & Havinga, P. J. M. (2008). Algorithms for energy efficient data extraction from wireless sensor networks for environmental monitoring applications. In L. Kooistra, & A. Ligtenberg (Eds.), Proceedings of International Workshop Sensing a Changing World 2008 (pp. 15-18). (CGI report; No. CGI-08-005). Wageningen: Wageningen University and Research Centre.
    Chatterjea, Supriyo ; Havinga, Paul J.M. / Algorithms for energy efficient data extraction from wireless sensor networks for environmental monitoring applications. Proceedings of International Workshop Sensing a Changing World 2008. editor / L Kooistra ; A Ligtenberg. Wageningen : Wageningen University and Research Centre, 2008. pp. 15-18 (CGI report; CGI-08-005).
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    title = "Algorithms for energy efficient data extraction from wireless sensor networks for environmental monitoring applications",
    abstract = "Wireless sensor networks (WSNs) can provide high resolution spatial and temporal data for environmental applications if they are densely deployed. However, as the nodes which make up the network are typically battery operated, a major problem faced by WSNs is limited network lifetime. In order to extend network lifetime to several years, the radio transceiver and attached sensors need to be managed carefully to minimize power consumption. This paper provides an overview of two separate solutions that we are currently testing in a real-life application on the Great Barrier Reef (GBR). The first algorithm minimizes transmissions by taking advantage of spatial correlations of sensor readings while the second algorithm minimizes sensor sampling operations by taking advantage of the temporal correlations that exist between successive sensor readings. Both the solutions have been developed as part of our efforts together with the Australian Institute of Marine Science, to deploy a large scale WSN on the Great Barrier Reef (GBR). This network will be used to study the effects of global warming and agriculture on the coral reefs. Details of our deployment of sensor nodes on the GBR using buoys are also described.",
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    Chatterjea, S & Havinga, PJM 2008, Algorithms for energy efficient data extraction from wireless sensor networks for environmental monitoring applications. in L Kooistra & A Ligtenberg (eds), Proceedings of International Workshop Sensing a Changing World 2008. CGI report, no. CGI-08-005, Wageningen University and Research Centre, Wageningen, pp. 15-18.

    Algorithms for energy efficient data extraction from wireless sensor networks for environmental monitoring applications. / Chatterjea, Supriyo; Havinga, Paul J.M.

    Proceedings of International Workshop Sensing a Changing World 2008. ed. / L Kooistra; A Ligtenberg. Wageningen : Wageningen University and Research Centre, 2008. p. 15-18 (CGI report; No. CGI-08-005).

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

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    N2 - Wireless sensor networks (WSNs) can provide high resolution spatial and temporal data for environmental applications if they are densely deployed. However, as the nodes which make up the network are typically battery operated, a major problem faced by WSNs is limited network lifetime. In order to extend network lifetime to several years, the radio transceiver and attached sensors need to be managed carefully to minimize power consumption. This paper provides an overview of two separate solutions that we are currently testing in a real-life application on the Great Barrier Reef (GBR). The first algorithm minimizes transmissions by taking advantage of spatial correlations of sensor readings while the second algorithm minimizes sensor sampling operations by taking advantage of the temporal correlations that exist between successive sensor readings. Both the solutions have been developed as part of our efforts together with the Australian Institute of Marine Science, to deploy a large scale WSN on the Great Barrier Reef (GBR). This network will be used to study the effects of global warming and agriculture on the coral reefs. Details of our deployment of sensor nodes on the GBR using buoys are also described.

    AB - Wireless sensor networks (WSNs) can provide high resolution spatial and temporal data for environmental applications if they are densely deployed. However, as the nodes which make up the network are typically battery operated, a major problem faced by WSNs is limited network lifetime. In order to extend network lifetime to several years, the radio transceiver and attached sensors need to be managed carefully to minimize power consumption. This paper provides an overview of two separate solutions that we are currently testing in a real-life application on the Great Barrier Reef (GBR). The first algorithm minimizes transmissions by taking advantage of spatial correlations of sensor readings while the second algorithm minimizes sensor sampling operations by taking advantage of the temporal correlations that exist between successive sensor readings. Both the solutions have been developed as part of our efforts together with the Australian Institute of Marine Science, to deploy a large scale WSN on the Great Barrier Reef (GBR). This network will be used to study the effects of global warming and agriculture on the coral reefs. Details of our deployment of sensor nodes on the GBR using buoys are also described.

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    Chatterjea S, Havinga PJM. Algorithms for energy efficient data extraction from wireless sensor networks for environmental monitoring applications. In Kooistra L, Ligtenberg A, editors, Proceedings of International Workshop Sensing a Changing World 2008. Wageningen: Wageningen University and Research Centre. 2008. p. 15-18. (CGI report; CGI-08-005).