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An Approximate Data Collection Algorithm in Space-Based Internet of Things

  • Changjiang FeiEmail author
  • Baokang Zhao
  • Wanrong Yu
  • Chunqing Wu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11637)

Abstract

Space-based Internet of Things (S-IoT) is an important way to realize the real interconnection of all things because of its global coverage, infrastructure independence and strong resistance to destruction. In the S-IoT, a large amount of sensory data needs to be transmitted through a space-based information network with severely limited resources, which poses a great challenge to data collection. Therefore, this paper proposes an approximate data collection algorithm for the S-IoT, namely the sampling-reconstruction (SR) algorithm. The SR algorithm only collects the sensory data of some nodes, and then reconstructs the unacquired sensory data by leveraging the spatio-temporal correlation between sensory data, thereby reducing the amount of data that needs to be transmitted. We evaluated the performance of SR algorithm using real weather data set. The experimental results show that the SR algorithm can effectively reduce the amount of data collected under the condition of satisfying required data collection accuracy.

Keywords

Sensory data collection Space-based Internet of Things Internet of Things Spectral clustering Spatio-temporal compressive sensing 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Changjiang Fei
    • 1
    Email author
  • Baokang Zhao
    • 1
  • Wanrong Yu
    • 1
  • Chunqing Wu
    • 1
  1. 1.College of ComputerNational University of Defense TechnologyChangshaChina

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