• DocumentCode
    149671
  • Title

    Improving the accuracy of simulation models for localization schemes

  • Author

    Ibrahim, Walid M. ; Ali, Najah Abu ; Taha, Abd-Elhamid M. ; Hassanein, Hossam S.

  • Author_Institution
    Sch. of Comput., Queen´s Univ., Kingston, ON, Canada
  • fYear
    2014
  • fDate
    21-24 April 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Localization plays a substantial role in the future Internet, especially within the context of the Internet of Things (IoT). Increased dependence on devices and sensed data presses for more efficient and accurate localization schemes. In the IoT environment the area covered is large making it impossible to localize all devices and Sensor Nodes (SNs) using single-hop localization techniques. A solution to this problem is to use a multi-hop localization technique to estimate devices´ positions. Simulating localization techniques for wireless sensor networks is required in order to reduce cost and study the difference between localization techniques easily especially if the simulated environment is large. Thus a realistic model is required to simulate the localization process as accurately as possible. Many multi-hop localization techniques use Received Signal Strength Indicator (RSSI) to estimate the distance between SNs. Our interest in this work is to enhance the validation of these schemes prior to deployment. Specifically, we propose the use of a more realistic model for generating RSSI values. The model is based on practical measurements and is validated through extensive simulation.
  • Keywords
    Internet of Things; sensor placement; wireless sensor networks; Internet of Things; RSSI; device positions; future Internet; localization schemes; multihop localization technique; received signal strength indicator; sensor nodes; simulated environment; simulation models; single-hop localization techniques; wireless sensor networks; Distance measurement; Educational institutions; Gaussian distribution; Mathematical model; Measurement uncertainty; Noise; Tin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2014 IEEE Ninth International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4799-2842-2
  • Type

    conf

  • DOI
    10.1109/ISSNIP.2014.6827654
  • Filename
    6827654