• DocumentCode
    141720
  • Title

    A Spanning Tree Based Data Collection for Real-Time Streaming Sensor Data

  • Author

    Kyung Tae Kim ; Jong Chang Park ; Manyun Kim ; Ung Mo Kim ; Hee Yong Youn

  • Author_Institution
    Coll. of Inf. & Commun. Eng., Sungkyunkwan Univ., Suwon, South Korea
  • fYear
    2014
  • fDate
    24-27 Aug. 2014
  • Firstpage
    202
  • Lastpage
    207
  • Abstract
    Wireless sensor networks are widely used for gathering data in the distributed fashion. Since the network consists of low-cost nodes of limited battery power, it is a challenging task to design an energy efficient routing scheme. In this paper we propose a novel clustering algorithm based on spanning tree of bounded degree in each cluster for energy efficient WSNs. The proposed scheme selects the cluster-head considering the residual energy of each node, and partitions each cluster for constructing efficient routing paths to the base station. Computer simulation shows that the proposed scheme effectively reduces and balances the energy consumption among the nodes, and thus significantly extends the network lifetime compared to the existing schemes such as LEACH, PEGASIS, and TREEPSI.
  • Keywords
    data handling; digital simulation; energy conservation; energy consumption; pattern clustering; trees (mathematics); wireless sensor networks; cluster-head; clustering algorithm; computer simulation; energy consumption; energy efficient WSNs; energy efficient routing scheme; network lifetime; real-time streaming sensor data; routing paths; spanning tree based data collection; wireless sensor networks; Data collection; Data communication; Energy consumption; Energy efficiency; Protocols; Routing; Wireless sensor networks; Clustering; Real-time Streaming Data; Spanning Tree; Transmission Delay; Wireless Sensor Networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Dependable, Autonomic and Secure Computing (DASC), 2014 IEEE 12th International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-1-4799-5078-2
  • Type

    conf

  • DOI
    10.1109/DASC.2014.44
  • Filename
    6945689