• DocumentCode
    2411184
  • Title

    On-Demand Deployment Algorithm for a Hybrid Sensor Network

  • Author

    Shiu, Liang-Cheng ; Lee, Chao-yang ; Song, Tian-Wen ; Yang, Chu-Sing

  • Author_Institution
    Dept. of Inf. Technol., Nat. Pingtung Inst. of Commerce, Pingtung
  • Volume
    2
  • fYear
    2008
  • fDate
    17-20 Dec. 2008
  • Firstpage
    697
  • Lastpage
    702
  • Abstract
    Sensor deployment is one of the most fundamental and important issues in wireless sensor networks. Most of the current researches are concentrated on deploying static sensors or mobile sensors to improve coverage. This paper proposes on-demand centralized deployment algorithms in a hybrid sensor network which consists of both static and mobile sensors. The key feature is that on-demand deploying process is started by an event-driven request. A mobile sensor will be selected to heal coverage hole, on account of the priority of the Hole and the distance between the mobile sensor and the Hole. According to selection mobile sensors strategy is preemptive or not, the algorithms can present the different advantages of reducing the moving distance or reducing the response time, respectively, i.e., it has a characteristic with adaptability. Simulation result shows that the proposed approach differs from previous methods in which average moving distance and network lifetime are both improved for deploying sensors.
  • Keywords
    wireless sensor networks; event-driven request; hybrid sensor network; mobile sensors; on-demand centralized deployment algorithm; on-demand deployment algorithm; sensor deployment; static sensors; wireless sensor networks; Chaos; Computer science; Delay; Energy consumption; IP networks; Information technology; Sensor phenomena and characterization; US Department of Commerce; Ubiquitous computing; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Embedded and Ubiquitous Computing, 2008. EUC '08. IEEE/IFIP International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3492-3
  • Type

    conf

  • DOI
    10.1109/EUC.2008.124
  • Filename
    4755306