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

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Security, Privacy, and Anonymity in Computation, Communication, and Storage (SpaCCS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11637))

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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.

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Authors and Affiliations

  1. College of Computer, National University of Defense Technology, Changsha, 410073, China

    Changjiang Fei, Baokang Zhao, Wanrong Yu & Chunqing Wu

Authors
  1. Changjiang Fei
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  2. Baokang Zhao
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  3. Wanrong Yu
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  4. Chunqing Wu
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Corresponding author

Correspondence to Changjiang Fei .

Editor information

Editors and Affiliations

  1. Guangzhou University, Guangzhou, China

    Guojun Wang

  2. Huazhong University of Science and Technology, Wuhan, China

    Jun Feng

  3. Fordham University, New York City, NY, USA

    Md Zakirul Alam Bhuiyan

  4. University of New Brunswick, Fredericton, NB, Canada

    Rongxing Lu

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Fei, C., Zhao, B., Yu, W., Wu, C. (2019). An Approximate Data Collection Algorithm in Space-Based Internet of Things. In: Wang, G., Feng, J., Bhuiyan, M., Lu, R. (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2019. Lecture Notes in Computer Science(), vol 11637. Springer, Cham. https://doi.org/10.1007/978-3-030-24900-7_14

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  • DOI: https://doi.org/10.1007/978-3-030-24900-7_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24899-4

  • Online ISBN: 978-3-030-24900-7

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