• DocumentCode
    3414059
  • Title

    Efficient k-Dominant Skyline Processing in Wireless Sensor Networks

  • Author

    Huang, Jianmei ; Xin, Junchang ; Wang, Guoren ; Li, Miao

  • Author_Institution
    Key Lab. of Med. Image Comput., Northeastern Univ., Shenyang, China
  • Volume
    3
  • fYear
    2009
  • fDate
    12-14 Aug. 2009
  • Firstpage
    289
  • Lastpage
    294
  • Abstract
    Wireless sensor network amalgamates sensing, computing and communication technologies. Because of the energy limitation of sensor nodes, how to manage the data collected by the sensor nodes energy-efficiently becomes the focus of the research recently. As the main mean of multi-decision and data mining, skyline query plays a more and more important role in sensing applications. However, as the increase of data dimensionality, skyline query results extend greatly, which not only obstacles the decision, but also costs most of the energy of the nodes. In this article, k-dominant skyline query is researched deeply to deal with the above problem. An energy-efficient k-dominant skyline query algorithm (EKS) is proposed to calculate the k-dominant skyline of the wireless sensor network. The experimental results show that EKS could reduce the communication cost of the sensor network,while it calculates the k-dominant skyline, therefore, prolong the life-span of it.
  • Keywords
    data mining; query processing; wireless sensor networks; data mining; energy-efficient k-dominant skyline query algorithm; multidecision; skyline processing; wireless sensor networks; Algorithm design and analysis; Batteries; Communications technology; Computer networks; Energy efficiency; Energy management; Fires; Monitoring; Temperature sensors; Wireless sensor networks; skyline; wireless sensor network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-0-7695-3745-0
  • Type

    conf

  • DOI
    10.1109/HIS.2009.273
  • Filename
    5254584