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Clustering intelligent transportation sensors using public transportation

Author

Listed:
  • Tejswaroop Geetla

    (University at Buffalo (SUNY))

  • Rajan Batta

    (University at Buffalo (SUNY)
    Center for Transportation Injury Research, CUBRC)

  • Alan Blatt

    (Center for Transportation Injury Research, CUBRC)

  • Marie Flanigan

    (Center for Transportation Injury Research, CUBRC)

  • Kevin Majka

    (Center for Transportation Injury Research, CUBRC)

Abstract

Advanced transportation sensors use a wireless medium to communicate and use data fusion techniques to provide complete information. Large-scale use of intelligent transportation sensors can lead to data bottlenecks in an ad-hoc wireless sensor network, which needs to be reliable and should provide a framework to sensors that constantly join and leave the network. A possible solution is to use public transportation vehicles as data fusion nodes or cluster heads. This paper presents a mathematical programming approach to use public transportation vehicles as cluster heads. The mathematical programming solution seeks to maximize benefit achieved by covering both mobile and stationary sensors, while considering cost/penalty associated with changing cluster head locations. A simulation is developed to capture realistic considerations of a transportation network. This simulation is used to validate the solution provided by the mathematical model.

Suggested Citation

  • Tejswaroop Geetla & Rajan Batta & Alan Blatt & Marie Flanigan & Kevin Majka, 2016. "Clustering intelligent transportation sensors using public transportation," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 594-611, October.
    • Handle: RePEc:spr:topjnl:v:24:y:2016:i:3:d:10.1007_s11750-016-0410-7
    DOI: 10.1007/s11750-016-0410-7
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    References listed on IDEAS

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    1. Dipesh J. Patel & Rajan Batta & Rakesh Nagi, 2005. "Clustering Sensors in Wireless Ad Hoc Networks Operating in a Threat Environment," Operations Research, INFORMS, vol. 53(3), pages 432-442, June.
    2. Erdemir, Elif Tokar & Batta, Rajan & Spielman, Seth & Rogerson, Peter A. & Blatt, Alan & Flanigan, Marie, 2008. "Location coverage models with demand originating from nodes and paths: Application to cellular network design," European Journal of Operational Research, Elsevier, vol. 190(3), pages 610-632, November.
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