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Deployment Optimization of Perception Layer Nodes in the Internet of Things Based on NB-IoT Technology

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Abstract

The traditional deployment optimization method of perception layer nodes in the Internet of Things has the drawbacks of poor optimization performance. Therefore, this paper proposes a research on deployment optimization of perception layer nodes in the Internet of Things based on NB-loT technology. The genetic algorithm is used to code the nodes in the perception layer of the Internet of Things, and the initial population is determined. Based on the coding of the nodes in the perception layer and the initial population, the fitness function is designed, and the NB-loT technology is used to optimize the deployment of the nodes in the perception layer of the Internet of Things. Experiments show that the average coverage of the proposed method is 24% higher than that of the traditional method, which shows that the proposed method has better optimization performance.

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Correspondence to Ming-hao Ding .

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Liu, R., Shen, Jr., Jiao, F., Ding, Mh. (2021). Deployment Optimization of Perception Layer Nodes in the Internet of Things Based on NB-IoT Technology. In: Liu, S., Xia, L. (eds) Advanced Hybrid Information Processing. ADHIP 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 348. Springer, Cham. https://doi.org/10.1007/978-3-030-67874-6_19

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  • DOI: https://doi.org/10.1007/978-3-030-67874-6_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67873-9

  • Online ISBN: 978-3-030-67874-6

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