Research Article
Deployment Optimization of Perception Layer Nodes in the Internet of Things Based on NB-IoT Technology
@INPROCEEDINGS{10.1007/978-3-030-67874-6_19, author={Rui Liu and Jie-ran Shen and Feng Jiao and Ming-hao Ding}, title={Deployment Optimization of Perception Layer Nodes in the Internet of Things Based on NB-IoT Technology}, proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2021}, month={1}, keywords={Internet of things Perception layer Node Deployment Optimization}, doi={10.1007/978-3-030-67874-6_19} }- Rui Liu
Jie-ran Shen
Feng Jiao
Ming-hao Ding
Year: 2021
Deployment Optimization of Perception Layer Nodes in the Internet of Things Based on NB-IoT Technology
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-67874-6_19
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.
