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Scattered data selection for dense sensor networks

Published: 26 April 2004 Publication History

Abstract

An evaluation methodology is presented for the performance of reporting node self-selection in wireless sensor networks. Five cost metrics are proposed along with several methods for self-selection that involve little or no collaboration with other nodes. These costs are used to evaluate how efficiently the various algorithms allow for node self-selection as simulated on different field complexities. Analysis of different methods over 100 test fields sampled by 2000 nodes indicates that there is no single method that is superior in all respects. Trade-offs in latency and overall energy consumption are revealed to be highly dependent on the selection method and the field complexity.

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Cited By

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  • (2016)IntroductionWireless Sensor Networks10.1007/978-3-319-46769-6_1(1-22)Online publication date: 3-Nov-2016
  • (2010)Areas covered with Probability Bound in wireless sensor networks2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)10.1109/ICACTE.2010.5579338(V4-465-V4-469)Online publication date: Aug-2010
  • (2009)Efficient sensor selection based on spatial correlation in wireless sensor networks2009 14th International CSI Computer Conference10.1109/CSICC.2009.5349649(627-632)Online publication date: Oct-2009
  • Show More Cited By

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  1. Scattered data selection for dense sensor networks

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    cover image ACM Conferences
    IPSN '04: Proceedings of the 3rd international symposium on Information processing in sensor networks
    April 2004
    464 pages
    ISBN:1581138466
    DOI:10.1145/984622
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 26 April 2004

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    Author Tags

    1. data recovery
    2. energy measures
    3. sensor networks

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    Cited By

    View all
    • (2016)IntroductionWireless Sensor Networks10.1007/978-3-319-46769-6_1(1-22)Online publication date: 3-Nov-2016
    • (2010)Areas covered with Probability Bound in wireless sensor networks2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)10.1109/ICACTE.2010.5579338(V4-465-V4-469)Online publication date: Aug-2010
    • (2009)Efficient sensor selection based on spatial correlation in wireless sensor networks2009 14th International CSI Computer Conference10.1109/CSICC.2009.5349649(627-632)Online publication date: Oct-2009
    • (2008)Efficient gathering of correlated data in sensor networksACM Transactions on Sensor Networks10.1145/1325651.13256554:1(1-31)Online publication date: 11-Feb-2008
    • (2008)Sensor selection for target tracking in WSN Using Modified INS algorithm2008 3rd International Conference on Information and Communication Technologies: From Theory to Applications10.1109/ICTTA.2008.4530051(1-6)Online publication date: May-2008
    • (2007)Isolines: efficient spatio‐temporal data aggregation in sensor networksWireless Communications and Mobile Computing10.1002/wcm.5519:3(357-367)Online publication date: 28-Aug-2007
    • (2006)Contour mapsComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2005.09.03850:15(2820-2838)Online publication date: 18-Oct-2006
    • (2005)Ef.cient Continuous Mapping in Sensor Networks Using IsolinesProceedings of the The Second Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services10.1109/MOBIQUITOUS.2005.26(325-332)Online publication date: 17-Jul-2005

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