• DocumentCode
    2298782
  • Title

    A Level-Based Energy Efficiency Clustering Approach for Wireless Sensor Networks

  • Author

    Chu, Hung-Chi ; Liao, Ying-Hsiang ; Chang, Lin-Huang ; Chao, Fang-Lin

  • Author_Institution
    Dept. of Inf. & Commun. Eng., Chaoyang Univ. of Technol., Taichung, Taiwan
  • fYear
    2009
  • fDate
    7-9 July 2009
  • Firstpage
    324
  • Lastpage
    329
  • Abstract
    In wireless sensor networks, energy efficiency is an important research issue. The data transmission times could be decreased effectively to achieve energy efficiency by applying a cluster-based structure. This study proposed a level-based energy efficiency clustering approach. Each cluster replaces its cluster head and re-clusters periodically according to the established energy level. A cluster head is a node that has more residual energy and lower communication cost compared to other nodes. This level-based energy efficiency clustering approach could decrease the replacement times of cluster heads, thus avoiding the excessive energy consumption caused by frequent replacement of cluster heads. The simulation results showed that this approach has less energy consumption and can effectively extend the network lifetime.
  • Keywords
    statistical analysis; telecommunication network reliability; wireless sensor networks; WSN lifetime; data transmission; energy consumption; level-based energy efficiency clustering approach; wireless sensor network; Chaotic communication; Computer networks; Costs; Energy consumption; Energy efficiency; Energy states; Head; Pervasive computing; Space technology; Wireless sensor networks; cluster; energy efficiency; wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Ubiquitous, Autonomic and Trusted Computing, 2009. UIC-ATC '09. Symposia and Workshops on
  • Conference_Location
    Brisbane, QLD
  • Print_ISBN
    978-1-4244-4902-6
  • Electronic_ISBN
    978-0-7695-3737-5
  • Type

    conf

  • DOI
    10.1109/UIC-ATC.2009.28
  • Filename
    5319218